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Building an Analytics Engine on MongoDB to Revolutionize Advertising

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The document discusses the development of Yallzi, an analytics engine using MongoDB designed to enhance the advertising experience by connecting consumers with local vendors and sharing favorite places. It outlines the challenges faced during the project's journey, including the need for real-time analytics, a robust database structure, and multi-language support, emphasizing the goal of making recommendations based on user preferences and location. The ultimate vision is to create a seamless platform for users to explore new cities while facilitating meaningful interactions between vendors and consumers.

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Building an Analytics Engine on MongoDB to Revolutionize Advertising @ Yallzi /crowd-Fun the Internet
“Hello (MongoDB) World!” Steve and ALL@YALLZI { “title”: ”yallzi@yallzi”, “email”: ”steve@yallzi.com”, “linkedin”: ”https://www.linkedin.com/in/stevebond”, “twitter”: [“company”: “@YALLZI”, “personal”: “@TheOneTechie”], “web”: “yallzi.com”, "location": "garage/Austin_TX" }
Agenda / About / Challenges, requirements / Journey / Outcome, next /crowd-Fun the audience
About /crowd-Fun the moderator
Who are you?
/about
/about
Crowd-Fun the internet. Started *not* that long ago... in a galaxy that involved moving from NYC to Austin 1. Lost all local NYC hangouts over two short nights 2. Is there a guide to living like an Austin local and get to know business owners? 3. No excuses not to unpack boxes. We asked ourselves: Why there is no app for this? /about Dreaming of.. - Not Unpacking! - Cold Beer - Movie, - Local Museum - BBQ! I am in Texas... Can’t a local just share the best places to hangout and let me chat vendors up ??!
/about I want to Share my City: “My Stay-cation is someone’s perfect Vacation”: I’m searching for an easier way to help others experience the town I love. Family and friends constantly ask for recommendations for their visits. They share these with their friends and families… and then I get calls from people they’ve shared it with who I don’t even know. AND at the worst times of the day. There’s gotta be an easier way to share the town I love… I want Advertising that works for me: “Invite vendors to your dialogue” I am not sure which venues to select. I wish I could have a dialogue with multiple vendors to help me pick the best spots for my group and needs… I wish my vendors fought for my business, maybe through hand-picked discounts and freebies? I’m sure they would like this personal connection too. I want to Explore New Cities: “Someone’s Stay-cation is my perfect Vacation” I am planning a vacation. We love traveling like locals. Hours of scouring the web for perfect places are turning to weeks… This is becoming a second job! We just want to find a local’s perfect staycation. Isn’t there an easier way for me to experience Places others love?
/jɑːlzi:/ YALLZI /about
Building an Analytics Engine on MongoDB to Revolutionize Advertising
YALLZI helps you share all your favorite places with friends or the whole world. YALLZI helps you explore new worlds that other Yallziers have shared. YALLZI breaks the barrier between Vendor and Consumer. /about Vision
/Challenges, Requirements
/challenges, requirements Strength-Skills ● C, C++, Java ● Product Development ● Content Management ● SQL - Any RDBMS since mid 1990s ● NoSQL - 5 years of dev and prod ● Data Warehousing ● Ad Servers and Analytics ● Proven ability to squeeze 4 weeks of work out of 7 days of free demo version ● Mean Extra Dry Martini’s
/challenges, requirements Needs ● Data set of POI covering major verticals in US and International ● Ensure parallel development of web, iOS and Android apps ● APP that does not need a lot of design work initially but will tell a story and please investors ● Multi-language support ● Save Time and Money on Everything ● Lighting fast speed : ○ vision → prototype → alpha/beta → GA ○ iterate ○ scale ○ data and geo data retrieval ○ DB is NOT a bottleneck for frequent app builds ● Close to real time analytics collection and processing to power apps
/challenges, requirements ● Data set of POI covering major verticals in US and International -- FACTUAL, US Based POI ● Ensure parallel development of web, iOS and Android apps ● APP that does not need a lot of design work initially but will tell a story and please investors ● Multi-language support ● Save Time and Money on Everything ● Lighting fast speed : ○ vision → prototype → alpha/beta → GA ○ iterate ○ scale ○ data and geo data retrieval ○ DB is NOT a bottleneck for frequent app builds ● Close to real time analytics collection and processing to power apps Solutions
/challenges, requirements Solutions ● Data set of POI covering major verticals in US and International -- FACTUAL, US Based POI ● Ensure parallel development of web, iOS and Android apps RESTful dev ● APP that does not need a lot of design work initially but will tell a story and please investors ● Multi-language support ● Save Time and Money on Everything ● Lighting fast speed : ○ vision → prototype → alpha/beta → GA ○ iterate ○ scale ○ data and geo data retrieval ○ DB is NOT a bottleneck for frequent app builds ● Close to real time analytics collection and processing to power apps
/challenges, requirements ● Data set of POI covering major verticals in US and International -- FACTUAL, US Based POI ● Ensure parallel development of web, iOS and Android apps RESTful dev ● APP that does not need a lot of design … Hold Expensive Design - go simple ● Multi-language support ● Save Time and Money on Everything ● Lighting fast speed : ○ vision → prototype → alpha/beta → GA ○ iterate ○ scale ○ data and geo data retrieval ○ DB is NOT a bottleneck for frequent app builds ● Close to real time analytics collection and processing to power apps Solutions
/challenges, requirements ● Data set of POI covering major verticals in US and International -- FACTUAL, US Based POI ● Ensure parallel development of web, iOS and Android apps RESTful dev ● APP that does not need a lot of design … Hold Expensive Design - go simple ● Multi-language support Pick A DB! ● Save Time and Money on Everything ● Lighting fast speed : ○ vision → prototype → alpha/beta → GA ○ iterate ○ scale ○ data and geo data retrieval ○ DB is NOT a bottleneck for frequent app builds ● Close to real time analytics collection and processing to power apps Solutions
/challenges, requirements ● Data set of POI covering major verticals in US and International -- FACTUAL, US Based POI ● Ensure parallel development of web, iOS and Android apps RESTful dev ● APP that does not need a lot of design … Hold Expensive Design - go simple ● Multi-language support Pick A DB! ● Save Time and Money on Everything Go Open Source ● Lighting fast speed : ○ vision → prototype → alpha/beta → GA ○ iterate ○ scale ○ data and geo data retrieval ○ DB is NOT a bottleneck for frequent app builds ● Close to real time analytics collection and processing to power apps Solutions
/challenges, requirements ● Data set of POI covering major verticals in US and International -- FACTUAL, US Based POI ● Ensure parallel development of web, iOS and Android apps RESTful dev ● APP that does not need a lot of design … Hold Expensive Design - go simple ● Multi-language support Pick A DB! ● Save Time and Money on Everything Go Open Source ● Lighting fast speed : Pick A DB! ○ vision → prototype → alpha/beta → GA ○ iterate ○ scale ○ data and geo data retrieval ○ DB is NOT a bottleneck for frequent app builds ● Close to real time analytics collection and processing to power apps Solutions
● Data set of POI covering major verticals in US and International -- FACTUAL, US Based POI ● Ensure parallel development of web, iOS and Android apps RESTful dev ● APP that does not need a lot of design … Hold Expensive Design - go simple ● Multi-language support Pick A DB! ● Save Time and Money on Everything Go Open Source ● Lighting fast speed : Pick A DB! ○ vision → prototype → alpha/beta → GA ○ iterate ○ scale ○ data and geo data retrieval ○ DB is NOT a bottleneck for frequent app builds ● Close to real time analytics collection and processing to power apps Pick A DB! /challenges, requirements Solutions
- expressive query language - indexing- GeoIndexing - performance - scalability - flexibility - no need to learn new languages - easy to use management tools - a vendor behind the product - opensource / strong community - run well on Cloud (deployment architecture flexibility) /challenges, requirements Pick a DB... SQL noSQL
Select * from actors a, activities ac, history h where a.actorID=...
Selecting MongoDB ● Multi-language support ● Save Time and Money on Everything - Open Source/Supported by Vendor ● Lightning fast speed to ○ vision → prototype → alpha/beta → GA ○ iterate ○ scale ○ data and geo data retrieval ○ DB is NOT a bottleneck for frequent app builds ● Close to real-time analytics collection and processing to power apps /challenges, requirements
/Journey
● Database Selection - MongoDB 2.6 ● Design ○ DB’s: POI, Actors, Actor Activities(Analytics) ○ Access ○ Indexing ○ Availability ○ Scale ○ Flexibility ● Schema ○ Actors ○ Analytics ○ Advertising Secret Potion ○ Personalize This! ○ Deployment /journey Building BackEnd: Data Meets The App while both constantly Evolve
● Database Selection - MongoDB 2.6 ● Design ○ DB’s: POI, Actors, Actor Activities(Analytics) ○ Access : API ○ Indexing ○ Availability ○ Scale ○ Flexibility ● Schema ○ Actors ○ Analytics ○ Advertising Secret Potion ○ Personalize This! ○ Deployment /journey Building BackEnd: Data Meets The App while both constantly Evolve All calls are made as HTTP requests to one common backend residing on one URL and serviced by one application, so all calls will have a common prefix: http://<server>:<port>/api
● Database Selection - MongoDB 2.6 ● Design ○ DB’s: POI, Actors, Actor Activities(Analytics) ○ Access : API ○ Indexing: Frugal, don’t over-index to avoid degradation ○ Availability ○ Scale ○ Flexibility ● Schema ○ Actors ○ Analytics ○ Advertising Secret Potion ○ Personalize This! ○ Deployment /journey Building BackEnd: Data Meets The App while both constantly Evolve
● Database Selection - MongoDB 2.6 ● Design ○ DB’s: POI, Actors, Actor Activities(Analytics) ○ Access : API ○ Indexing: Frugal, don’t over-index to avoid degradation ○ Availability: 24/7 365 - revisit at deployment meeting ○ Scale ○ Flexibility ● Schema ○ Actors ○ Analytics ○ Advertising Secret Potion ○ Personalize This! ○ Deployment /journey Building BackEnd: Data Meets The App while both constantly Evolve
● Database Selection - MongoDB 2.6 ● Design ○ DB’s: POI, Actors, Actor Activities(Analytics) ○ Access : API ○ Indexing: Frugal, don’t over-index to avoid degradation ○ Availability: 24/7 365 - revisit at deployment meeting ○ Scale: targeting 100,000 active users in 3-6 months ○ Flexibility ● Schema ○ Actors ○ Analytics ○ Advertising Secret Potion ○ Personalize This! ○ Deployment /journey Building BackEnd: Data Meets The App while both constantly Evolve
● Database Selection - MongoDB 2.6 ● Design ○ DB’s: POI, Actors, Actor Activities(Analytics) ○ Access : API ○ Indexing: Frugal, don’t over-index to avoid degradation ○ Availability: 24/7 365 - revisit at deployment meeting ○ Scale: targeting 100,000 active users in 3-6 months ○ Flexibility : Don’t throw kitchen sink in DB. Keep DB’s collections as slim as possible ● Schema ○ Actors ○ Analytics ○ Advertising Secret Potion ○ Personalize This! ○ Deployment /journey Building BackEnd: Data Meets The App while both constantly Evolve
● Database Selection - MongoDB 2.6 ● Design ○ DB’s: POI, Actors, Actor Activities(Analytics) ○ Access : API ○ Indexing: Frugal, don’t over-index to avoid degradation ○ Availability: 24/7 365 - revisit at deployment meeting ○ Scale: targeting 100,000 active users in 3-6 months ○ Flexibility : Don’t throw kitchen sink in DB. Keep DB’s collections as slim as possible ● Schema ○ Actors ○ Analytics ○ Advertising Secret Potion ○ Personalize This! ○ Deployment /journey Building BackEnd: Data Meets The App while both constantly Evolve
1. Location (Dynamic) a. geo : latitude, longitude (geoLocation) 2. Preferences (Historical & “Acquired”) a. Existing preference - Bob loves bicycling followed by a beer and lives on UES... A fellow Yallzier just biked East River Greenway, followed by a beer at Pony Bar. Yallzi renders this plan to Bob. - A fellow Yallzier Has Shared Interests and fellow Yalzier is a referrer a. Shared - Bob and Sue both like Mexican, Sue loves Rosa Mexicana. Yallzi asks, Will Bob?) - Sue has similar interests and is a referer a. Adjacent and could be “Acquired” - Bob likes Ballets and Opera. Sue loves this + Broadway Show. Yallzi suggest Broadway show) - Sue has similar interests and is a referrer 1. Availability (Dynamic) a. time { "message": "", "status": "OK", "auth": “156D66FE8B9097A336DF325589837E674B”, “data”: { “user”: { “name”: “Yallzier”, “email”: “yallzi@yallzi.com”, “phone”: “+1-2121212121”, “socialLogin”: “FACEBOOK_Yallzier”, “deviceToken”: [ “appleToken123”, “appleToken234”, ... ]} } } /journey /api/v2/user/getDetails Actors(Consumers) Parameters String auth: authentication token previously received double lat: latitude of users current position long: longitude of users current position
1. Location (Dynamic) a. geo : latitude, longitude (geoLocation) 2. Preferences (Historical & “Acquired”) a. Existing preference - Bob loves bicycling followed by a beer and lives on UES... A fellow Yallzier just biked East River Greenway, followed by a beer at Pony Bar. Yallzi renders this plan to Bob. - A fellow Yallzier Has Shared Interests and fellow Yalzier is a referrer a. Shared - Bob and Sue both like Mexican, Sue loves Rosa Mexicana. Yallzi asks, Will Bob?) - Sue has similar interests and is a referer a. Adjacent and could be “Acquired” - Bob likes Ballets and Opera. Sue loves this + Broadway Show. Yallzi suggest Broadway show) - Sue has similar interests and is a referrer 1. Availability (Dynamic) a. time { "message": "", "status": "OK", "auth": “156D66FE8B9097A336DF325589837E674B”, “data”: { “user”: { “name”: “Yallzier”, “email”: “yallzi@yallzi.com”, “phone”: “+1-2121212121”, “socialLogin”: “FACEBOOK_Yallzier”, “deviceToken”: [ “appleToken123”, “appleToken234”, ... ]} } } /journey Actors(Consumers) /api/v2/user/getDetails Parameters String auth: authentication token previously received double lat: latitude of users current position long: longitude of users current position
1. Location (Dynamic) a. geo : latitude, longitude (geoLocation) 1. Preferences (Historical & “Acquired”) a. Existing preference - Bob loves bicycling followed by a beer and lives on UES... A fellow Yallzier just biked East River Greenway, followed by a beer at Pony Bar. Yallzi renders this plan to Bob. - A fellow Yallzier Has Shared Interests and fellow Yalzier is a referrer a. Shared - Bob and Sue both like Mexican, Sue loves Rosa Mexicana. Yallzi asks, Will Bob?) - Sue has similar interests and is a referer a. Adjacent and could be “Acquired” - Bob likes Ballets and Opera. Sue loves this + Broadway Show. Yallzi suggest Broadway show) - Sue has similar interests and is a referrer 1. Availability (Dynamic) /journey { "message": "", "status": "OK", "auth": “156D66FE8B9097A336DF325589837E674B”, “data”: { “user”: { “name”: “Yallzier”, “email”: “yallzi@yallzi.com”, “phone”: “+1-2121212121”, “socialLogin”: “FACEBOOK_Yallzier”, “deviceToken”: [ “appleToken123”, “appleToken234”, ... ]} } } Parameters String auth: authentication token previously received double lat: latitude of users current position long: longitude of users current position /api/v2/user/getDetails Actors(Consumers) Parameters String auth: authentication token previously received double lat: latitude of users current position long: longitude of users current position
1. Location (Dynamic) a. geo : latitude, longitude (geoLocation) 1. Preferences (Historical & “Acquired”) a. Existing preference - Bob loves bicycling followed by a beer and lives on UES... A fellow Yallzier just biked East River Greenway, followed by a beer at Pony Bar. Yallzi renders this plan to Bob. - A fellow Yallzier Has Shared Interests and fellow Yalzier is a referrer a. Shared - Bob and Sue both like Mexican, Sue loves Rosa Mexicana. Yallzi asks, Will Bob?) - Sue has similar interests and is a referer a. Adjacent and could be “Acquired” - Bob likes Ballets and Opera. Sue loves this + Broadway Show. Yallzi suggest Broadway show) - Sue has similar interests and is a referrer 1. Availability (Dynamic) /journey { "message": "", "status": "OK", "auth": “156D66FE8B9097A336DF325589837E674B”, “data”: { “user”: { “name”: “Yallzier”, “email”: “yallzi@yallzi.com”, “phone”: “+1-2121212121”, “socialLogin”: “FACEBOOK_Yallzier”, “deviceToken”: [ “appleToken123”, “appleToken234”, ... ]} } } Parameters String auth: authentication token previously received double lat: latitude of users current position long: longitude of users current position Actors(Consumers) /api/v2/user/getDetails
1. Location (Static) 2. Vertical (Static) a. Food & Dining b. Recreation c. Entertainment d. Arts & Culture e. Sports 3. Category a. Mexican 4. Offerings-Deals (dynamic) 5. Hours /journey { "message": "", "status": "OK", "data": { "date": "10/26/14",! "deals": [ { "dealId": “DINE_184a2409-7d4c-4854-ad1c-e7de099064ee", "name": "Porfirio’s Tacos",! "imageUrl": "http://api.yallzi.com/api/resources/rest.png", "address": "1512 Holly Street", "locality": "Austin", "postcode": "78703", "country": "us", "type": "Restaurant", "locationId": "184a2409-7d4c-4854-ad1c-e7de099064ee", "latitude": 30.255314, "longitude": -97.730564, "details": "", "amount": 0, "distance": 0.8936700034260777, "categoryLabels": [ [ "Mexicanl", “Tex Mex” ], ... ], "hours": { "monday": [ ]}.... Parameters: String auth: authentication token double lat: latitude of users current position double long: longitude of users current position" String verticalId int numberOfPeople: number of participants" long date: time stamp of event start" double distance: search radius double searchLat, if different from users current position double searchLong, if different from users current position Actors(Vendors) /api/v2/deal/list
1. Location (Static) 2. Vertical (Static) a. Food & Dining b. Recreation c. Entertainment d. Arts & Culture e. Sports 3. Category a. Mexican 4. Offerings-Deals (dynamic) 5. Hours /journey { "message": "", "status": "OK", "data": { "date": "10/26/14",! "deals": [ { "dealId": “DINE_184a2409-7d4c-4854-ad1c-e7de099064ee", "name": "Porfirio’s Tacos",! "imageUrl": "http://api.yallzi.com/api/resources/rest.png", "address": "1512 Holly Street", "locality": "Austin", "postcode": "78703", "country": "us", "type": "Restaurant", "locationId": "184a2409-7d4c-4854-ad1c-e7de099064ee", "latitude": 30.255314, "longitude": -97.730564, "details": "", "amount": 0, "distance": 0.8936700034260777, "categoryLabels": [ [ "Mexicanl", “Tex Mex” ], ... ], "hours": { "monday": [ ]}.... Parameters: String auth: authentication token double lat: latitude of users current position double long: longitude of users current position" String verticalId int numberOfPeople: number of participants" long date: time stamp of event start" double distance: search radius double searchLat, if different from users current position double searchLong, if different from users current position /api/v2/deal/list Actors(Vendors)
1. Location (Static) 2. Vertical (Static) a. Food & Dining b. Recreation c. Entertainment d. Arts & Culture e. Sports 3. Category a. Mexican 4. Offerings-Deals (dynamic) 5. Hours /journey { "message": "", "status": "OK", "data": { "date": "10/26/14",! "deals": [ { "dealId": “DINE_184a2409-7d4c-4854-ad1c-e7de099064ee", "name": "Porfirio’s Tacos",! "imageUrl": "http://api.yallzi.com/api/resources/rest.png", "address": "1512 Holly Street", "locality": "Austin", "postcode": "78703", "country": "us", "type": "Restaurant", "locationId": "184a2409-7d4c-4854-ad1c-e7de099064ee", "latitude": 30.255314, "longitude": -97.730564, "details": "", "amount": 0, "distance": 0.8936700034260777, "categoryLabels": [ [ "Mexicanl", “Tex Mex” ], ... ], "hours": { "monday": [ ]}.... Parameters: String auth: authentication token double lat: latitude of users current position double long: longitude of users current position" String verticalId int numberOfPeople: number of participants" long date: time stamp of event start" double distance: search radius double searchLat, if different from users current position double searchLong, if different from users current position Actors(Vendors) /api/v2/deal/list
● Database Selection - MongoDB 2.6->3.0. DB size decreased by 70% ● Design ○ DB’s: POI, Actors, Actor Activities(Analytics) ○ Access : API ○ Indexing: Frugal, don’t over-index to avoid degradation ○ Availability: 24/7 365 - revisit at deployment meeting ○ Scale: targeting 100,000 active users in 3-6 months ○ Flexibility : Don’t throw kitchen sink in DB. Keep DB’s collections as slim as possible ● Schema ○ Actors ○ Analytics ○ Advertising Secret Potion ○ Personalize This! ○ Deployment /journey Building BackEnd: Data Meets The App while both constantly Evolve
● Database Selection - MongoDB 3.0 ● Design ○ DB’s: POI, Actors, Actor Activities(Analytics) ○ Access : API ○ Indexing: Frugal, don’t over-index to avoid degradation ○ Availability: 24/7 365 - revisit at deployment meeting ○ Scale: targeting 100,000 active users in 3-6 months ○ Flexibility : Don’t throw kitchen sink in DB. Keep DB’s collections as slim as possible ● Schema ○ Actors ○ Analytics ○ Advertising Secret Potion ○ Personalize This! ○ Deployment /journey Building BackEnd: Data Meets The App while both constantly Evolve
Analytics an·a·lyt·ics /ˌanl’itiks / noun 1. the systematic computational analysis of data or statistics. o information resulting from the systematic analysis of data or statistics. We are Analyzing the ACTOR ACTIVITIES through Referrers and Referrals and Following… We analyze ● intent( following) ● checkIn ( confirmed at the place) ● Scoop( reviews, after the visit) With emphasis on people voting with their “feet” /journey
User Activities include ● intent to do stuff and/or share it ● intent to “borrow” or reuse of these plans ● Checked in Activities of Referrers ● Checked in Activities of Followers { "message": "", "status": "OK", "auth": “156D66FE8B9097A336DF325589837E674B”,! “data”: [ { “id”: “abcdef1234”, “referral”: “abcdefabcdef” ...}, ...] } /journey Referrer/Referral new Concept
/journey { "message": "", "status": "OK", "auth": “156D66FE8B9097A336DF325589837E674B”,! “data”: [ { “id”: “abcdef1234”, “referral”: “abcdefabcdef” ...}, ...] } User Activities include ● intent to do stuff and/or share it ● intent to “borrow” or reuse of these plans ● Checked in Activities of Referrers ● Checked in Activities of Followers Referrer/Referral new Concept
User Activities include ● intent to do stuff and/or share it ● intent to “borrow” or reuse of these plans ● Checked in Activities of Referrers ● Checked in Activities of Followers /journey { "message": "", "status": "OK", "auth": “156D66FE8B9097A336DF325589837E674B”,! “data”: [ { “id”: “abcdef1234”, “referral”: “abcdefabcdef” ...}, ...] } Referrer/Referral new Concept
User Activities include ● intent to do stuff and/or share it ● intent to “borrow” or reuse of these plans ● Checked in Activities of Referrers ● Checked in Activities of Followers /journey { "message": "", "status": "OK", "auth": “156D66FE8B9097A336DF325589837E674B”,! “data”: [ { “id”: “abcdef1234”, “referral”: “abcdefabcdef” ...}, ...] } Referrer/Referral new Concept
Analytics ... And ... Secret Potion: Yallzi enables: ● suggestions in your current or desired location that match your interests ● suggestions for “acquired” interests (delta between having common and different preferences) ● identification of emerging trends ● preparation for personal recommendations based on your and people with common interests behavior ● identification of new ratings model (people vote with their feet) /journey
● Activities collection is sharable ● Initial activity owner is a Referrer. Referrals are ‘followed” ● Vote signifies acceptance ● Ratings and Reviews=People Vote with their feet + Comments- is mined and analyzed real time /journey { "message": "", "status": "OK", "auth": “156D66FE8B9097A336DF325589837E674B”, “data”: { “id”: “xxx”, “date”: 1445901561064,! “dealId”: “yyy”, “YallziID”: [“xxx1”, “xxx2”, ...], “groupId”: “541f149be4b0c4c655ad5721”, “referral”: “12345677”, “votes”: [ “bead43122” : 0, “edba43edf” : 1 ], “comments”: [ { “user” : “ab12345678901234567”, “timestamp” : 14455667788, “text” : “This is a comment” }, ... ]} api/v2/yallzi/get Activity Log PARAMs: String auth: authentication token previously received Double lat: latitude of users current position Double long: longitude of users current position" String yallziId: event to update"
/journey { "message": "", "status": "OK", "auth": “156D66FE8B9097A336DF325589837E674B”, “data”: { “id”: “xxx”, “date”: 1445901561064,! “dealId”: “yyy”, “YallziID”: [“xxx1”, “xxx2”, ...], “groupId”: “541f149be4b0c4c655ad5721”, “referral”: “12345677”, “votes”: [ “bead43122” : 0, “edba43edf” : 1 ], “comments”: [ { “user” : “ab12345678901234567”, “timestamp” : 14455667788, “text” : “This is a comment” }, ... ]} ● Activities collection is sharable ● Initial activity owner is a Referrer. Referrals are ‘followed” ● Vote signifies acceptance ● Ratings and Reviews=People Vote with their feet + Comments- is mined and analyzed real time api/v2/yallzi/get Activity Log PARAMs: String auth: authentication token previously received Double lat: latitude of users current position Double long: longitude of users current position" String yallziId: event to update"
/journey { "message": "", "status": "OK", "auth": “156D66FE8B9097A336DF325589837E674B”, “data”: { “id”: “xxx”, “date”: 1445901561064,! “dealId”: “yyy”, “YallziID”: [“xxx1”, “xxx2”, ...], “groupId”: “541f149be4b0c4c655ad5721”, “referral”: “12345677”, “votes”: [ “bead43122” : 0, “edba43edf” : 1 ], “comments”: [ { “user” : “ab12345678901234567”, “timestamp” : 14455667788, “text” : “This is a comment” }, ... ]} ● Activities collection is sharable ● Initial activity owner is a Referrer. Referrals are ‘followed” ● Vote signifies acceptance ● Ratings and Reviews=People Vote with their feet + Comments- is mined and analyzed real time api/v2/yallzi/get Activity Log PARAMs: String auth: authentication token previously received Double lat: latitude of users current position Double long: longitude of users current position" String yallziId: event to update"
/journey Actor Activity { "message": "", "status": "OK", "auth": “156D66FE8B9097A336DF325589837E674B”, “data”: { “id”: “xxx”, “date”: 1445901561064,! “dealId”: “yyy”, “YallziID”: [“xxx1”, “xxx2”, ...], “groupId”: “541f149be4b0c4c655ad5721”, “referral”: “12345677”, “votes”: [ “bead43122” : 0, “edba43edf” : 1 ], “comments”: [ { “user” : “ab12345678901234567”, “timestamp” : 14455667788, “text” : “This is a comment” }, ... ]} PARAMs: String auth: authentication token previously received double lat: latitude of users current position double long: longitude of users current position" String yallziId: event to update" ● Activities collection is sharable ● Initial activity owner is a Referrer. Referrals are ‘followed” ● Vote signifies acceptance ● Ratings and Reviews=People Vote with their feet + Comments- is mined and analyzed real time api/v2/yallzi/get
● Database Selection - MongoDB 3.0 ● Design ○ DB’s: POI, Actors, Actor Activities(Analytics) ○ Access : API ○ Indexing: Frugal, don’t over-index to avoid degradation ○ Availability: 24/7 365 - revisit at deployment meeting ○ Scale: targeting 100,000 active users in 3-6 months ○ Flexibility : Don’t throw kitchen sink in DB. Keep DB’s collections as slim as possible ● Schema ○ Actors ○ Analytics ○ Advertising Secret Potion ○ Personalize This! ○ Deployment /journey Building BackEnd: Data Meets The App while both constantly Evolve
{{ "message": "", "status": "OK", "auth": “156D66FE8B9097A336DF325589837E674B”, “data”: { “id”: “xxx”, “date”: 1445901561064,! “dealId”: “yyy”,! “children”: [“xxx1”, “xxx2”, ...] “groupId”: “541f149be4b0c4c655ad5721”, “referral”: “12345677”, “votes”: [ “bead43122” : 0, “edba43edf” : 1 ], “comments”: [ { “user” : “ab12345678901234567”, “timestamp” : 14455667788, “text” : “Looking for a table for 1” }, ... /journey Vendor Direct Messaging ● Message - Direct Interaction with the vendor (online) ● Consumer initiates bidirectional conversation with business/brand ● Analyzed to provide service ● Can be private or public and become a hospitality message that all consumers can view by interacting with a link.
/journey Vendor Direct Messaging ● Message - Direct Interaction with the vendor (online) ● Consumer initiates bidirectional conversation with business/brand ● Analyzed to provide service ● Can be private or public and become a hospitality message that all consumers can view by interacting with a link.
{{ "message": "", "status": "OK", "auth": “156D66FE8B9097A336DF325589837E674B”, “data”: { “id”: “xxx”, “date”: 1445901561064,! “dealId”: “yyy”,! “children”: [“xxx1”, “xxx2”, ...], “groupId”: “541f149be4b0c4c655ad5721”, “referral”: “12345677”, “votes”: [ “bead43122” : 0, “edba43edf” : 1 ], “comments”: [ { “user” : “ab12345678901234567”, “timestamp” : 14455667788, “text” : “table for 1,quiet place?” }, ... /journey Vendor Direct Messaging ● Message - Direct Interaction with the vendor (online) ● Consumer initiates bidirectional conversation with business/brand ● Analyzed to provide service ● Can be private or public and become a hospitality message that all consumers can view by interacting with a link.
{{ "message": "", "status": "OK", "auth": “156D66FE8B9097A336DF325589837E674B”, “data”: { “id”: “xxx”, “date”: 1445901561064,! “dealId”: “yyy”,! “children”: [“xxx1”, “xxx2”, ...], “groupId”: “541f149be4b0c4c655ad5721”, “referral”: “12345677”, “votes”: [ “bead43122” : 0, “edba43edf” : 1 ], “comments”: [ { “user” : “ab12345678901234567”, “timestamp” : 14455667788, “text” : “table for 1,quiet place?” }, ... /journey Vendor Direct Messaging ● Message - Direct Interaction with the vendor (online) ● Consumer initiates bidirectional conversation with business/brand ● Analyzed to provide service ● Can be private or public and become a hospitality message that all consumers can view by interacting with a link.
● Database Selection - MongoDB 3.0 ● Design ○ DB’s: POI, Actors, Actor Activities(Analytics) ○ Access : API ○ Indexing: Frugal, don’t over-index to avoid degradation ○ Availability: 24/7 365 - revisit at deployment meeting ○ Scale: targeting 100,000 active users in 3-6 months ○ Flexibility : Don’t throw kitchen sink in DB. Keep DB’s collections as slim as possible ● Schema ○ Actors ○ Analytics ○ Advertising Secret Potion ○ Personalize This! ○ Deployment /journey Building BackEnd: Data Meets The App while both constantly Evolve
Personal “funBox” Collection ● Your most frequent referrers can be pre-processed ○ Yallzi personal “funBox” /journey Grouping and Deltas {WIP} Will include: - Plans of most frequently used referrers - Does not require any action on user part - Analyses Yallzier’s activity log
● Database Selection - MongoDB 3.0 ● Design ○ DB’s: POI, Actors, Actor Activities(Analytics) ○ Access : API ○ Indexing: Frugal, don’t over-index to avoid degradation ○ Availability: 24/7 365 - revisit at deployment meeting ○ Scale: targeting 100,000 active users in 3-6 months ○ Flexibility : Don’t throw kitchen sink in DB. Keep DB’s collections as slim as possible ● Schema ○ Actors ○ Analytics ○ Advertising Secret Potion ○ Personalize This! ○ Deployment : AWS, MMS /journey Building BackEnd: Data Meets The App while both constantly Evolve
● Database Selection - MongoDB 3.0 ● Design ○ DB’s: POI, Actors, Actor Activities(Analytics) ○ Access : API ○ Indexing: Frugal, don’t over-index to avoid degradation ○ Availability: 24/7 365 - revisit at deployment meeting ○ Scale: targeting 100,000 active users in 3-6 months ○ Flexibility : Don’t throw kitchen sink in DB. Keep DB’s collections as slim as possible ● Schema ○ Actors ○ Analytics ○ Advertising Secret Potion ○ Personalize This! ○ Deployment : AWS, MMS /journey Building BackEnd: Data Meets The App while both constantly Evolve
Outcome, Next and Recap
Outcome - Dream to Prototype : 2.5 weeks - Prototype to Alpha: 1 month - iOS App development: ~5 months - Android App development: ~ 2 months - Suspended - Rebranded and Pivoted 5 months into Dev. Adjust within 2 weeks - Beta Releases: twice a week - AWS hosting $36 a month - MongoDB : rock solid /outcome, next
Recap (our lessons) - MongoDB is great fit for bootstrapped startUps like Yallzi or for an innovative project with aggressive goals - Take risks, but stick to the following: - Simplify everything from storage to aggregation downstream - Understand what you are storing and where (vis a vis static and dynamic data) - Determine what data will be made public/private - Don’t go Index happy - Flexibility is not throwing the kitchen sink in DB. Flexibility is for growth and dynamics of your business. - Overuse of database strengths can create a big SPOF - Simplify access patterns/abstract - If it is too easy to do, you might not have thought of something - Have fun! It will work! /outcome, next
What’s Next - Development: - Completing within next few weeks - Beta launch: - Follow us on Twitter @Yallzi or @TheOneTechie for the date to install the app and Crowd-Fun the internet - We are looking for partners and developers - Funding : - We are going strong for the first prize in crowdfunding drives - We are in conversations with TX based accelerators - We love talking to investors even those who want to say NO! - Community: - We are looking for advise and happy to share our thoughts - Future: - See y’all on Yallzi and at MongoDB World next year - Philosophy: - Do one thing, do it right, test, repeat! /outcome, next
Hit is on Twitter - @YALLZI - @TheOneTechie Yes, We’re Hiring: - http://yallzi.com/internships/ Eureka Moments: - http://yallzi.com/internships/our-eureka-moments/ Angel Profile: - https://angel.co/yallzi On Social Choice Data: - https://www.linkedin.com/pulse/article/social-choice-data-steve-bond - https://www.linkedin.com/pulse/how-do-groups-decide-social-choice- data-part-2-steve-bond On App Adoption: - https://www.linkedin.com/pulse/article/first-date-app-steve-bond - https://www.linkedin.com/pulse/article/userapp-dating-steve-bond Holly Street Garage, Austin, Texas ---------------------------------------------- Also Found on: KickStarter, LaunchLeader, CrunchBase.. and other fine ‘net sites /outcome, next
Thank you
/Tricks Actually, there are no tricks, whatsoever… except - be “lazy” developers making the best of the tools we build - provide users, be they sharers, benefactors, or business owners with simple tools: - map and ‘save’ their most memorable moments and share it with y’all - see others best memorable moments - reach out to vendors to invite them into the conversation For this we needed a thought through, light-weight and flexible model that allows us to build/add additional artifacts and store them. We also decided to bank of reverse of Similar Interests and see if people might want to discover stuff they never experiences before. We are still working on it We are looking forward to learn from reputable companies and scrappy startUps!
What challenges do you solve when you don’t get paid for it? ● A revolution in combining social choice data with behavioral data that results in Kick Ass User Experience ● New Dimension of Advertising ● We don’t reinvent the wheel, even though we tried 17 times and came up with helium inflatable wheels supporting a beach chair with 2 beers and my puppy than annoys me when I work /What We Do
#startUp Recent SCRUM NOTES ● “Man, where did all those competitors come from?” ● VC Breaking News: said they Loved the idea and we definitely should.. call them after we have 1 million DL’s. ● Alerts: Looks like we hacked our own bank account but due to error in the code we left 23 cents. Whose code is it, i don’t care whose money.. ● Battle of API versus App developer is won by API. After all: iPhone processing power is probably greater than our server!

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Building an Analytics Engine on MongoDB to Revolutionize Advertising

  • 1. Building an Analytics Engine on MongoDB to Revolutionize Advertising @ Yallzi /crowd-Fun the Internet
  • 2. “Hello (MongoDB) World!” Steve and ALL@YALLZI { “title”: ”yallzi@yallzi”, “email”: ”steve@yallzi.com”, “linkedin”: ”https://www.linkedin.com/in/stevebond”, “twitter”: [“company”: “@YALLZI”, “personal”: “@TheOneTechie”], “web”: “yallzi.com”, "location": "garage/Austin_TX" }
  • 3. Agenda / About / Challenges, requirements / Journey / Outcome, next /crowd-Fun the audience
  • 8. Crowd-Fun the internet. Started *not* that long ago... in a galaxy that involved moving from NYC to Austin 1. Lost all local NYC hangouts over two short nights 2. Is there a guide to living like an Austin local and get to know business owners? 3. No excuses not to unpack boxes. We asked ourselves: Why there is no app for this? /about Dreaming of.. - Not Unpacking! - Cold Beer - Movie, - Local Museum - BBQ! I am in Texas... Can’t a local just share the best places to hangout and let me chat vendors up ??!
  • 9. /about I want to Share my City: “My Stay-cation is someone’s perfect Vacation”: I’m searching for an easier way to help others experience the town I love. Family and friends constantly ask for recommendations for their visits. They share these with their friends and families… and then I get calls from people they’ve shared it with who I don’t even know. AND at the worst times of the day. There’s gotta be an easier way to share the town I love… I want Advertising that works for me: “Invite vendors to your dialogue” I am not sure which venues to select. I wish I could have a dialogue with multiple vendors to help me pick the best spots for my group and needs… I wish my vendors fought for my business, maybe through hand-picked discounts and freebies? I’m sure they would like this personal connection too. I want to Explore New Cities: “Someone’s Stay-cation is my perfect Vacation” I am planning a vacation. We love traveling like locals. Hours of scouring the web for perfect places are turning to weeks… This is becoming a second job! We just want to find a local’s perfect staycation. Isn’t there an easier way for me to experience Places others love?
  • 12. YALLZI helps you share all your favorite places with friends or the whole world. YALLZI helps you explore new worlds that other Yallziers have shared. YALLZI breaks the barrier between Vendor and Consumer. /about Vision
  • 14. /challenges, requirements Strength-Skills ● C, C++, Java ● Product Development ● Content Management ● SQL - Any RDBMS since mid 1990s ● NoSQL - 5 years of dev and prod ● Data Warehousing ● Ad Servers and Analytics ● Proven ability to squeeze 4 weeks of work out of 7 days of free demo version ● Mean Extra Dry Martini’s
  • 15. /challenges, requirements Needs ● Data set of POI covering major verticals in US and International ● Ensure parallel development of web, iOS and Android apps ● APP that does not need a lot of design work initially but will tell a story and please investors ● Multi-language support ● Save Time and Money on Everything ● Lighting fast speed : ○ vision → prototype → alpha/beta → GA ○ iterate ○ scale ○ data and geo data retrieval ○ DB is NOT a bottleneck for frequent app builds ● Close to real time analytics collection and processing to power apps
  • 16. /challenges, requirements ● Data set of POI covering major verticals in US and International -- FACTUAL, US Based POI ● Ensure parallel development of web, iOS and Android apps ● APP that does not need a lot of design work initially but will tell a story and please investors ● Multi-language support ● Save Time and Money on Everything ● Lighting fast speed : ○ vision → prototype → alpha/beta → GA ○ iterate ○ scale ○ data and geo data retrieval ○ DB is NOT a bottleneck for frequent app builds ● Close to real time analytics collection and processing to power apps Solutions
  • 17. /challenges, requirements Solutions ● Data set of POI covering major verticals in US and International -- FACTUAL, US Based POI ● Ensure parallel development of web, iOS and Android apps RESTful dev ● APP that does not need a lot of design work initially but will tell a story and please investors ● Multi-language support ● Save Time and Money on Everything ● Lighting fast speed : ○ vision → prototype → alpha/beta → GA ○ iterate ○ scale ○ data and geo data retrieval ○ DB is NOT a bottleneck for frequent app builds ● Close to real time analytics collection and processing to power apps
  • 18. /challenges, requirements ● Data set of POI covering major verticals in US and International -- FACTUAL, US Based POI ● Ensure parallel development of web, iOS and Android apps RESTful dev ● APP that does not need a lot of design … Hold Expensive Design - go simple ● Multi-language support ● Save Time and Money on Everything ● Lighting fast speed : ○ vision → prototype → alpha/beta → GA ○ iterate ○ scale ○ data and geo data retrieval ○ DB is NOT a bottleneck for frequent app builds ● Close to real time analytics collection and processing to power apps Solutions
  • 19. /challenges, requirements ● Data set of POI covering major verticals in US and International -- FACTUAL, US Based POI ● Ensure parallel development of web, iOS and Android apps RESTful dev ● APP that does not need a lot of design … Hold Expensive Design - go simple ● Multi-language support Pick A DB! ● Save Time and Money on Everything ● Lighting fast speed : ○ vision → prototype → alpha/beta → GA ○ iterate ○ scale ○ data and geo data retrieval ○ DB is NOT a bottleneck for frequent app builds ● Close to real time analytics collection and processing to power apps Solutions
  • 20. /challenges, requirements ● Data set of POI covering major verticals in US and International -- FACTUAL, US Based POI ● Ensure parallel development of web, iOS and Android apps RESTful dev ● APP that does not need a lot of design … Hold Expensive Design - go simple ● Multi-language support Pick A DB! ● Save Time and Money on Everything Go Open Source ● Lighting fast speed : ○ vision → prototype → alpha/beta → GA ○ iterate ○ scale ○ data and geo data retrieval ○ DB is NOT a bottleneck for frequent app builds ● Close to real time analytics collection and processing to power apps Solutions
  • 21. /challenges, requirements ● Data set of POI covering major verticals in US and International -- FACTUAL, US Based POI ● Ensure parallel development of web, iOS and Android apps RESTful dev ● APP that does not need a lot of design … Hold Expensive Design - go simple ● Multi-language support Pick A DB! ● Save Time and Money on Everything Go Open Source ● Lighting fast speed : Pick A DB! ○ vision → prototype → alpha/beta → GA ○ iterate ○ scale ○ data and geo data retrieval ○ DB is NOT a bottleneck for frequent app builds ● Close to real time analytics collection and processing to power apps Solutions
  • 22. ● Data set of POI covering major verticals in US and International -- FACTUAL, US Based POI ● Ensure parallel development of web, iOS and Android apps RESTful dev ● APP that does not need a lot of design … Hold Expensive Design - go simple ● Multi-language support Pick A DB! ● Save Time and Money on Everything Go Open Source ● Lighting fast speed : Pick A DB! ○ vision → prototype → alpha/beta → GA ○ iterate ○ scale ○ data and geo data retrieval ○ DB is NOT a bottleneck for frequent app builds ● Close to real time analytics collection and processing to power apps Pick A DB! /challenges, requirements Solutions
  • 23. - expressive query language - indexing- GeoIndexing - performance - scalability - flexibility - no need to learn new languages - easy to use management tools - a vendor behind the product - opensource / strong community - run well on Cloud (deployment architecture flexibility) /challenges, requirements Pick a DB... SQL noSQL
  • 24. Select * from actors a, activities ac, history h where a.actorID=...
  • 25. Selecting MongoDB ● Multi-language support ● Save Time and Money on Everything - Open Source/Supported by Vendor ● Lightning fast speed to ○ vision → prototype → alpha/beta → GA ○ iterate ○ scale ○ data and geo data retrieval ○ DB is NOT a bottleneck for frequent app builds ● Close to real-time analytics collection and processing to power apps /challenges, requirements
  • 27. ● Database Selection - MongoDB 2.6 ● Design ○ DB’s: POI, Actors, Actor Activities(Analytics) ○ Access ○ Indexing ○ Availability ○ Scale ○ Flexibility ● Schema ○ Actors ○ Analytics ○ Advertising Secret Potion ○ Personalize This! ○ Deployment /journey Building BackEnd: Data Meets The App while both constantly Evolve
  • 28. ● Database Selection - MongoDB 2.6 ● Design ○ DB’s: POI, Actors, Actor Activities(Analytics) ○ Access : API ○ Indexing ○ Availability ○ Scale ○ Flexibility ● Schema ○ Actors ○ Analytics ○ Advertising Secret Potion ○ Personalize This! ○ Deployment /journey Building BackEnd: Data Meets The App while both constantly Evolve All calls are made as HTTP requests to one common backend residing on one URL and serviced by one application, so all calls will have a common prefix: http://<server>:<port>/api
  • 29. ● Database Selection - MongoDB 2.6 ● Design ○ DB’s: POI, Actors, Actor Activities(Analytics) ○ Access : API ○ Indexing: Frugal, don’t over-index to avoid degradation ○ Availability ○ Scale ○ Flexibility ● Schema ○ Actors ○ Analytics ○ Advertising Secret Potion ○ Personalize This! ○ Deployment /journey Building BackEnd: Data Meets The App while both constantly Evolve
  • 30. ● Database Selection - MongoDB 2.6 ● Design ○ DB’s: POI, Actors, Actor Activities(Analytics) ○ Access : API ○ Indexing: Frugal, don’t over-index to avoid degradation ○ Availability: 24/7 365 - revisit at deployment meeting ○ Scale ○ Flexibility ● Schema ○ Actors ○ Analytics ○ Advertising Secret Potion ○ Personalize This! ○ Deployment /journey Building BackEnd: Data Meets The App while both constantly Evolve
  • 31. ● Database Selection - MongoDB 2.6 ● Design ○ DB’s: POI, Actors, Actor Activities(Analytics) ○ Access : API ○ Indexing: Frugal, don’t over-index to avoid degradation ○ Availability: 24/7 365 - revisit at deployment meeting ○ Scale: targeting 100,000 active users in 3-6 months ○ Flexibility ● Schema ○ Actors ○ Analytics ○ Advertising Secret Potion ○ Personalize This! ○ Deployment /journey Building BackEnd: Data Meets The App while both constantly Evolve
  • 32. ● Database Selection - MongoDB 2.6 ● Design ○ DB’s: POI, Actors, Actor Activities(Analytics) ○ Access : API ○ Indexing: Frugal, don’t over-index to avoid degradation ○ Availability: 24/7 365 - revisit at deployment meeting ○ Scale: targeting 100,000 active users in 3-6 months ○ Flexibility : Don’t throw kitchen sink in DB. Keep DB’s collections as slim as possible ● Schema ○ Actors ○ Analytics ○ Advertising Secret Potion ○ Personalize This! ○ Deployment /journey Building BackEnd: Data Meets The App while both constantly Evolve
  • 33. ● Database Selection - MongoDB 2.6 ● Design ○ DB’s: POI, Actors, Actor Activities(Analytics) ○ Access : API ○ Indexing: Frugal, don’t over-index to avoid degradation ○ Availability: 24/7 365 - revisit at deployment meeting ○ Scale: targeting 100,000 active users in 3-6 months ○ Flexibility : Don’t throw kitchen sink in DB. Keep DB’s collections as slim as possible ● Schema ○ Actors ○ Analytics ○ Advertising Secret Potion ○ Personalize This! ○ Deployment /journey Building BackEnd: Data Meets The App while both constantly Evolve
  • 34. 1. Location (Dynamic) a. geo : latitude, longitude (geoLocation) 2. Preferences (Historical & “Acquired”) a. Existing preference - Bob loves bicycling followed by a beer and lives on UES... A fellow Yallzier just biked East River Greenway, followed by a beer at Pony Bar. Yallzi renders this plan to Bob. - A fellow Yallzier Has Shared Interests and fellow Yalzier is a referrer a. Shared - Bob and Sue both like Mexican, Sue loves Rosa Mexicana. Yallzi asks, Will Bob?) - Sue has similar interests and is a referer a. Adjacent and could be “Acquired” - Bob likes Ballets and Opera. Sue loves this + Broadway Show. Yallzi suggest Broadway show) - Sue has similar interests and is a referrer 1. Availability (Dynamic) a. time { "message": "", "status": "OK", "auth": “156D66FE8B9097A336DF325589837E674B”, “data”: { “user”: { “name”: “Yallzier”, “email”: “yallzi@yallzi.com”, “phone”: “+1-2121212121”, “socialLogin”: “FACEBOOK_Yallzier”, “deviceToken”: [ “appleToken123”, “appleToken234”, ... ]} } } /journey /api/v2/user/getDetails Actors(Consumers) Parameters String auth: authentication token previously received double lat: latitude of users current position long: longitude of users current position
  • 35. 1. Location (Dynamic) a. geo : latitude, longitude (geoLocation) 2. Preferences (Historical & “Acquired”) a. Existing preference - Bob loves bicycling followed by a beer and lives on UES... A fellow Yallzier just biked East River Greenway, followed by a beer at Pony Bar. Yallzi renders this plan to Bob. - A fellow Yallzier Has Shared Interests and fellow Yalzier is a referrer a. Shared - Bob and Sue both like Mexican, Sue loves Rosa Mexicana. Yallzi asks, Will Bob?) - Sue has similar interests and is a referer a. Adjacent and could be “Acquired” - Bob likes Ballets and Opera. Sue loves this + Broadway Show. Yallzi suggest Broadway show) - Sue has similar interests and is a referrer 1. Availability (Dynamic) a. time { "message": "", "status": "OK", "auth": “156D66FE8B9097A336DF325589837E674B”, “data”: { “user”: { “name”: “Yallzier”, “email”: “yallzi@yallzi.com”, “phone”: “+1-2121212121”, “socialLogin”: “FACEBOOK_Yallzier”, “deviceToken”: [ “appleToken123”, “appleToken234”, ... ]} } } /journey Actors(Consumers) /api/v2/user/getDetails Parameters String auth: authentication token previously received double lat: latitude of users current position long: longitude of users current position
  • 36. 1. Location (Dynamic) a. geo : latitude, longitude (geoLocation) 1. Preferences (Historical & “Acquired”) a. Existing preference - Bob loves bicycling followed by a beer and lives on UES... A fellow Yallzier just biked East River Greenway, followed by a beer at Pony Bar. Yallzi renders this plan to Bob. - A fellow Yallzier Has Shared Interests and fellow Yalzier is a referrer a. Shared - Bob and Sue both like Mexican, Sue loves Rosa Mexicana. Yallzi asks, Will Bob?) - Sue has similar interests and is a referer a. Adjacent and could be “Acquired” - Bob likes Ballets and Opera. Sue loves this + Broadway Show. Yallzi suggest Broadway show) - Sue has similar interests and is a referrer 1. Availability (Dynamic) /journey { "message": "", "status": "OK", "auth": “156D66FE8B9097A336DF325589837E674B”, “data”: { “user”: { “name”: “Yallzier”, “email”: “yallzi@yallzi.com”, “phone”: “+1-2121212121”, “socialLogin”: “FACEBOOK_Yallzier”, “deviceToken”: [ “appleToken123”, “appleToken234”, ... ]} } } Parameters String auth: authentication token previously received double lat: latitude of users current position long: longitude of users current position /api/v2/user/getDetails Actors(Consumers) Parameters String auth: authentication token previously received double lat: latitude of users current position long: longitude of users current position
  • 37. 1. Location (Dynamic) a. geo : latitude, longitude (geoLocation) 1. Preferences (Historical & “Acquired”) a. Existing preference - Bob loves bicycling followed by a beer and lives on UES... A fellow Yallzier just biked East River Greenway, followed by a beer at Pony Bar. Yallzi renders this plan to Bob. - A fellow Yallzier Has Shared Interests and fellow Yalzier is a referrer a. Shared - Bob and Sue both like Mexican, Sue loves Rosa Mexicana. Yallzi asks, Will Bob?) - Sue has similar interests and is a referer a. Adjacent and could be “Acquired” - Bob likes Ballets and Opera. Sue loves this + Broadway Show. Yallzi suggest Broadway show) - Sue has similar interests and is a referrer 1. Availability (Dynamic) /journey { "message": "", "status": "OK", "auth": “156D66FE8B9097A336DF325589837E674B”, “data”: { “user”: { “name”: “Yallzier”, “email”: “yallzi@yallzi.com”, “phone”: “+1-2121212121”, “socialLogin”: “FACEBOOK_Yallzier”, “deviceToken”: [ “appleToken123”, “appleToken234”, ... ]} } } Parameters String auth: authentication token previously received double lat: latitude of users current position long: longitude of users current position Actors(Consumers) /api/v2/user/getDetails
  • 38. 1. Location (Static) 2. Vertical (Static) a. Food & Dining b. Recreation c. Entertainment d. Arts & Culture e. Sports 3. Category a. Mexican 4. Offerings-Deals (dynamic) 5. Hours /journey { "message": "", "status": "OK", "data": { "date": "10/26/14",! "deals": [ { "dealId": “DINE_184a2409-7d4c-4854-ad1c-e7de099064ee", "name": "Porfirio’s Tacos",! "imageUrl": "http://api.yallzi.com/api/resources/rest.png", "address": "1512 Holly Street", "locality": "Austin", "postcode": "78703", "country": "us", "type": "Restaurant", "locationId": "184a2409-7d4c-4854-ad1c-e7de099064ee", "latitude": 30.255314, "longitude": -97.730564, "details": "", "amount": 0, "distance": 0.8936700034260777, "categoryLabels": [ [ "Mexicanl", “Tex Mex” ], ... ], "hours": { "monday": [ ]}.... Parameters: String auth: authentication token double lat: latitude of users current position double long: longitude of users current position" String verticalId int numberOfPeople: number of participants" long date: time stamp of event start" double distance: search radius double searchLat, if different from users current position double searchLong, if different from users current position Actors(Vendors) /api/v2/deal/list
  • 39. 1. Location (Static) 2. Vertical (Static) a. Food & Dining b. Recreation c. Entertainment d. Arts & Culture e. Sports 3. Category a. Mexican 4. Offerings-Deals (dynamic) 5. Hours /journey { "message": "", "status": "OK", "data": { "date": "10/26/14",! "deals": [ { "dealId": “DINE_184a2409-7d4c-4854-ad1c-e7de099064ee", "name": "Porfirio’s Tacos",! "imageUrl": "http://api.yallzi.com/api/resources/rest.png", "address": "1512 Holly Street", "locality": "Austin", "postcode": "78703", "country": "us", "type": "Restaurant", "locationId": "184a2409-7d4c-4854-ad1c-e7de099064ee", "latitude": 30.255314, "longitude": -97.730564, "details": "", "amount": 0, "distance": 0.8936700034260777, "categoryLabels": [ [ "Mexicanl", “Tex Mex” ], ... ], "hours": { "monday": [ ]}.... Parameters: String auth: authentication token double lat: latitude of users current position double long: longitude of users current position" String verticalId int numberOfPeople: number of participants" long date: time stamp of event start" double distance: search radius double searchLat, if different from users current position double searchLong, if different from users current position /api/v2/deal/list Actors(Vendors)
  • 40. 1. Location (Static) 2. Vertical (Static) a. Food & Dining b. Recreation c. Entertainment d. Arts & Culture e. Sports 3. Category a. Mexican 4. Offerings-Deals (dynamic) 5. Hours /journey { "message": "", "status": "OK", "data": { "date": "10/26/14",! "deals": [ { "dealId": “DINE_184a2409-7d4c-4854-ad1c-e7de099064ee", "name": "Porfirio’s Tacos",! "imageUrl": "http://api.yallzi.com/api/resources/rest.png", "address": "1512 Holly Street", "locality": "Austin", "postcode": "78703", "country": "us", "type": "Restaurant", "locationId": "184a2409-7d4c-4854-ad1c-e7de099064ee", "latitude": 30.255314, "longitude": -97.730564, "details": "", "amount": 0, "distance": 0.8936700034260777, "categoryLabels": [ [ "Mexicanl", “Tex Mex” ], ... ], "hours": { "monday": [ ]}.... Parameters: String auth: authentication token double lat: latitude of users current position double long: longitude of users current position" String verticalId int numberOfPeople: number of participants" long date: time stamp of event start" double distance: search radius double searchLat, if different from users current position double searchLong, if different from users current position Actors(Vendors) /api/v2/deal/list
  • 41. ● Database Selection - MongoDB 2.6->3.0. DB size decreased by 70% ● Design ○ DB’s: POI, Actors, Actor Activities(Analytics) ○ Access : API ○ Indexing: Frugal, don’t over-index to avoid degradation ○ Availability: 24/7 365 - revisit at deployment meeting ○ Scale: targeting 100,000 active users in 3-6 months ○ Flexibility : Don’t throw kitchen sink in DB. Keep DB’s collections as slim as possible ● Schema ○ Actors ○ Analytics ○ Advertising Secret Potion ○ Personalize This! ○ Deployment /journey Building BackEnd: Data Meets The App while both constantly Evolve
  • 42. ● Database Selection - MongoDB 3.0 ● Design ○ DB’s: POI, Actors, Actor Activities(Analytics) ○ Access : API ○ Indexing: Frugal, don’t over-index to avoid degradation ○ Availability: 24/7 365 - revisit at deployment meeting ○ Scale: targeting 100,000 active users in 3-6 months ○ Flexibility : Don’t throw kitchen sink in DB. Keep DB’s collections as slim as possible ● Schema ○ Actors ○ Analytics ○ Advertising Secret Potion ○ Personalize This! ○ Deployment /journey Building BackEnd: Data Meets The App while both constantly Evolve
  • 43. Analytics an·a·lyt·ics /ˌanl’itiks / noun 1. the systematic computational analysis of data or statistics. o information resulting from the systematic analysis of data or statistics. We are Analyzing the ACTOR ACTIVITIES through Referrers and Referrals and Following… We analyze ● intent( following) ● checkIn ( confirmed at the place) ● Scoop( reviews, after the visit) With emphasis on people voting with their “feet” /journey
  • 44. User Activities include ● intent to do stuff and/or share it ● intent to “borrow” or reuse of these plans ● Checked in Activities of Referrers ● Checked in Activities of Followers { "message": "", "status": "OK", "auth": “156D66FE8B9097A336DF325589837E674B”,! “data”: [ { “id”: “abcdef1234”, “referral”: “abcdefabcdef” ...}, ...] } /journey Referrer/Referral new Concept
  • 45. /journey { "message": "", "status": "OK", "auth": “156D66FE8B9097A336DF325589837E674B”,! “data”: [ { “id”: “abcdef1234”, “referral”: “abcdefabcdef” ...}, ...] } User Activities include ● intent to do stuff and/or share it ● intent to “borrow” or reuse of these plans ● Checked in Activities of Referrers ● Checked in Activities of Followers Referrer/Referral new Concept
  • 46. User Activities include ● intent to do stuff and/or share it ● intent to “borrow” or reuse of these plans ● Checked in Activities of Referrers ● Checked in Activities of Followers /journey { "message": "", "status": "OK", "auth": “156D66FE8B9097A336DF325589837E674B”,! “data”: [ { “id”: “abcdef1234”, “referral”: “abcdefabcdef” ...}, ...] } Referrer/Referral new Concept
  • 47. User Activities include ● intent to do stuff and/or share it ● intent to “borrow” or reuse of these plans ● Checked in Activities of Referrers ● Checked in Activities of Followers /journey { "message": "", "status": "OK", "auth": “156D66FE8B9097A336DF325589837E674B”,! “data”: [ { “id”: “abcdef1234”, “referral”: “abcdefabcdef” ...}, ...] } Referrer/Referral new Concept
  • 48. Analytics ... And ... Secret Potion: Yallzi enables: ● suggestions in your current or desired location that match your interests ● suggestions for “acquired” interests (delta between having common and different preferences) ● identification of emerging trends ● preparation for personal recommendations based on your and people with common interests behavior ● identification of new ratings model (people vote with their feet) /journey
  • 49. ● Activities collection is sharable ● Initial activity owner is a Referrer. Referrals are ‘followed” ● Vote signifies acceptance ● Ratings and Reviews=People Vote with their feet + Comments- is mined and analyzed real time /journey { "message": "", "status": "OK", "auth": “156D66FE8B9097A336DF325589837E674B”, “data”: { “id”: “xxx”, “date”: 1445901561064,! “dealId”: “yyy”, “YallziID”: [“xxx1”, “xxx2”, ...], “groupId”: “541f149be4b0c4c655ad5721”, “referral”: “12345677”, “votes”: [ “bead43122” : 0, “edba43edf” : 1 ], “comments”: [ { “user” : “ab12345678901234567”, “timestamp” : 14455667788, “text” : “This is a comment” }, ... ]} api/v2/yallzi/get Activity Log PARAMs: String auth: authentication token previously received Double lat: latitude of users current position Double long: longitude of users current position" String yallziId: event to update"
  • 50. /journey { "message": "", "status": "OK", "auth": “156D66FE8B9097A336DF325589837E674B”, “data”: { “id”: “xxx”, “date”: 1445901561064,! “dealId”: “yyy”, “YallziID”: [“xxx1”, “xxx2”, ...], “groupId”: “541f149be4b0c4c655ad5721”, “referral”: “12345677”, “votes”: [ “bead43122” : 0, “edba43edf” : 1 ], “comments”: [ { “user” : “ab12345678901234567”, “timestamp” : 14455667788, “text” : “This is a comment” }, ... ]} ● Activities collection is sharable ● Initial activity owner is a Referrer. Referrals are ‘followed” ● Vote signifies acceptance ● Ratings and Reviews=People Vote with their feet + Comments- is mined and analyzed real time api/v2/yallzi/get Activity Log PARAMs: String auth: authentication token previously received Double lat: latitude of users current position Double long: longitude of users current position" String yallziId: event to update"
  • 51. /journey { "message": "", "status": "OK", "auth": “156D66FE8B9097A336DF325589837E674B”, “data”: { “id”: “xxx”, “date”: 1445901561064,! “dealId”: “yyy”, “YallziID”: [“xxx1”, “xxx2”, ...], “groupId”: “541f149be4b0c4c655ad5721”, “referral”: “12345677”, “votes”: [ “bead43122” : 0, “edba43edf” : 1 ], “comments”: [ { “user” : “ab12345678901234567”, “timestamp” : 14455667788, “text” : “This is a comment” }, ... ]} ● Activities collection is sharable ● Initial activity owner is a Referrer. Referrals are ‘followed” ● Vote signifies acceptance ● Ratings and Reviews=People Vote with their feet + Comments- is mined and analyzed real time api/v2/yallzi/get Activity Log PARAMs: String auth: authentication token previously received Double lat: latitude of users current position Double long: longitude of users current position" String yallziId: event to update"
  • 52. /journey Actor Activity { "message": "", "status": "OK", "auth": “156D66FE8B9097A336DF325589837E674B”, “data”: { “id”: “xxx”, “date”: 1445901561064,! “dealId”: “yyy”, “YallziID”: [“xxx1”, “xxx2”, ...], “groupId”: “541f149be4b0c4c655ad5721”, “referral”: “12345677”, “votes”: [ “bead43122” : 0, “edba43edf” : 1 ], “comments”: [ { “user” : “ab12345678901234567”, “timestamp” : 14455667788, “text” : “This is a comment” }, ... ]} PARAMs: String auth: authentication token previously received double lat: latitude of users current position double long: longitude of users current position" String yallziId: event to update" ● Activities collection is sharable ● Initial activity owner is a Referrer. Referrals are ‘followed” ● Vote signifies acceptance ● Ratings and Reviews=People Vote with their feet + Comments- is mined and analyzed real time api/v2/yallzi/get
  • 53. ● Database Selection - MongoDB 3.0 ● Design ○ DB’s: POI, Actors, Actor Activities(Analytics) ○ Access : API ○ Indexing: Frugal, don’t over-index to avoid degradation ○ Availability: 24/7 365 - revisit at deployment meeting ○ Scale: targeting 100,000 active users in 3-6 months ○ Flexibility : Don’t throw kitchen sink in DB. Keep DB’s collections as slim as possible ● Schema ○ Actors ○ Analytics ○ Advertising Secret Potion ○ Personalize This! ○ Deployment /journey Building BackEnd: Data Meets The App while both constantly Evolve
  • 54. {{ "message": "", "status": "OK", "auth": “156D66FE8B9097A336DF325589837E674B”, “data”: { “id”: “xxx”, “date”: 1445901561064,! “dealId”: “yyy”,! “children”: [“xxx1”, “xxx2”, ...] “groupId”: “541f149be4b0c4c655ad5721”, “referral”: “12345677”, “votes”: [ “bead43122” : 0, “edba43edf” : 1 ], “comments”: [ { “user” : “ab12345678901234567”, “timestamp” : 14455667788, “text” : “Looking for a table for 1” }, ... /journey Vendor Direct Messaging ● Message - Direct Interaction with the vendor (online) ● Consumer initiates bidirectional conversation with business/brand ● Analyzed to provide service ● Can be private or public and become a hospitality message that all consumers can view by interacting with a link.
  • 55. /journey Vendor Direct Messaging ● Message - Direct Interaction with the vendor (online) ● Consumer initiates bidirectional conversation with business/brand ● Analyzed to provide service ● Can be private or public and become a hospitality message that all consumers can view by interacting with a link.
  • 56. {{ "message": "", "status": "OK", "auth": “156D66FE8B9097A336DF325589837E674B”, “data”: { “id”: “xxx”, “date”: 1445901561064,! “dealId”: “yyy”,! “children”: [“xxx1”, “xxx2”, ...], “groupId”: “541f149be4b0c4c655ad5721”, “referral”: “12345677”, “votes”: [ “bead43122” : 0, “edba43edf” : 1 ], “comments”: [ { “user” : “ab12345678901234567”, “timestamp” : 14455667788, “text” : “table for 1,quiet place?” }, ... /journey Vendor Direct Messaging ● Message - Direct Interaction with the vendor (online) ● Consumer initiates bidirectional conversation with business/brand ● Analyzed to provide service ● Can be private or public and become a hospitality message that all consumers can view by interacting with a link.
  • 57. {{ "message": "", "status": "OK", "auth": “156D66FE8B9097A336DF325589837E674B”, “data”: { “id”: “xxx”, “date”: 1445901561064,! “dealId”: “yyy”,! “children”: [“xxx1”, “xxx2”, ...], “groupId”: “541f149be4b0c4c655ad5721”, “referral”: “12345677”, “votes”: [ “bead43122” : 0, “edba43edf” : 1 ], “comments”: [ { “user” : “ab12345678901234567”, “timestamp” : 14455667788, “text” : “table for 1,quiet place?” }, ... /journey Vendor Direct Messaging ● Message - Direct Interaction with the vendor (online) ● Consumer initiates bidirectional conversation with business/brand ● Analyzed to provide service ● Can be private or public and become a hospitality message that all consumers can view by interacting with a link.
  • 58. ● Database Selection - MongoDB 3.0 ● Design ○ DB’s: POI, Actors, Actor Activities(Analytics) ○ Access : API ○ Indexing: Frugal, don’t over-index to avoid degradation ○ Availability: 24/7 365 - revisit at deployment meeting ○ Scale: targeting 100,000 active users in 3-6 months ○ Flexibility : Don’t throw kitchen sink in DB. Keep DB’s collections as slim as possible ● Schema ○ Actors ○ Analytics ○ Advertising Secret Potion ○ Personalize This! ○ Deployment /journey Building BackEnd: Data Meets The App while both constantly Evolve
  • 59. Personal “funBox” Collection ● Your most frequent referrers can be pre-processed ○ Yallzi personal “funBox” /journey Grouping and Deltas {WIP} Will include: - Plans of most frequently used referrers - Does not require any action on user part - Analyses Yallzier’s activity log
  • 60. ● Database Selection - MongoDB 3.0 ● Design ○ DB’s: POI, Actors, Actor Activities(Analytics) ○ Access : API ○ Indexing: Frugal, don’t over-index to avoid degradation ○ Availability: 24/7 365 - revisit at deployment meeting ○ Scale: targeting 100,000 active users in 3-6 months ○ Flexibility : Don’t throw kitchen sink in DB. Keep DB’s collections as slim as possible ● Schema ○ Actors ○ Analytics ○ Advertising Secret Potion ○ Personalize This! ○ Deployment : AWS, MMS /journey Building BackEnd: Data Meets The App while both constantly Evolve
  • 61. ● Database Selection - MongoDB 3.0 ● Design ○ DB’s: POI, Actors, Actor Activities(Analytics) ○ Access : API ○ Indexing: Frugal, don’t over-index to avoid degradation ○ Availability: 24/7 365 - revisit at deployment meeting ○ Scale: targeting 100,000 active users in 3-6 months ○ Flexibility : Don’t throw kitchen sink in DB. Keep DB’s collections as slim as possible ● Schema ○ Actors ○ Analytics ○ Advertising Secret Potion ○ Personalize This! ○ Deployment : AWS, MMS /journey Building BackEnd: Data Meets The App while both constantly Evolve
  • 63. Outcome - Dream to Prototype : 2.5 weeks - Prototype to Alpha: 1 month - iOS App development: ~5 months - Android App development: ~ 2 months - Suspended - Rebranded and Pivoted 5 months into Dev. Adjust within 2 weeks - Beta Releases: twice a week - AWS hosting $36 a month - MongoDB : rock solid /outcome, next
  • 64. Recap (our lessons) - MongoDB is great fit for bootstrapped startUps like Yallzi or for an innovative project with aggressive goals - Take risks, but stick to the following: - Simplify everything from storage to aggregation downstream - Understand what you are storing and where (vis a vis static and dynamic data) - Determine what data will be made public/private - Don’t go Index happy - Flexibility is not throwing the kitchen sink in DB. Flexibility is for growth and dynamics of your business. - Overuse of database strengths can create a big SPOF - Simplify access patterns/abstract - If it is too easy to do, you might not have thought of something - Have fun! It will work! /outcome, next
  • 65. What’s Next - Development: - Completing within next few weeks - Beta launch: - Follow us on Twitter @Yallzi or @TheOneTechie for the date to install the app and Crowd-Fun the internet - We are looking for partners and developers - Funding : - We are going strong for the first prize in crowdfunding drives - We are in conversations with TX based accelerators - We love talking to investors even those who want to say NO! - Community: - We are looking for advise and happy to share our thoughts - Future: - See y’all on Yallzi and at MongoDB World next year - Philosophy: - Do one thing, do it right, test, repeat! /outcome, next
  • 66. Hit is on Twitter - @YALLZI - @TheOneTechie Yes, We’re Hiring: - http://yallzi.com/internships/ Eureka Moments: - http://yallzi.com/internships/our-eureka-moments/ Angel Profile: - https://angel.co/yallzi On Social Choice Data: - https://www.linkedin.com/pulse/article/social-choice-data-steve-bond - https://www.linkedin.com/pulse/how-do-groups-decide-social-choice- data-part-2-steve-bond On App Adoption: - https://www.linkedin.com/pulse/article/first-date-app-steve-bond - https://www.linkedin.com/pulse/article/userapp-dating-steve-bond Holly Street Garage, Austin, Texas ---------------------------------------------- Also Found on: KickStarter, LaunchLeader, CrunchBase.. and other fine ‘net sites /outcome, next
  • 68. /Tricks Actually, there are no tricks, whatsoever… except - be “lazy” developers making the best of the tools we build - provide users, be they sharers, benefactors, or business owners with simple tools: - map and ‘save’ their most memorable moments and share it with y’all - see others best memorable moments - reach out to vendors to invite them into the conversation For this we needed a thought through, light-weight and flexible model that allows us to build/add additional artifacts and store them. We also decided to bank of reverse of Similar Interests and see if people might want to discover stuff they never experiences before. We are still working on it We are looking forward to learn from reputable companies and scrappy startUps!
  • 69. What challenges do you solve when you don’t get paid for it? ● A revolution in combining social choice data with behavioral data that results in Kick Ass User Experience ● New Dimension of Advertising ● We don’t reinvent the wheel, even though we tried 17 times and came up with helium inflatable wheels supporting a beach chair with 2 beers and my puppy than annoys me when I work /What We Do
  • 70. #startUp Recent SCRUM NOTES ● “Man, where did all those competitors come from?” ● VC Breaking News: said they Loved the idea and we definitely should.. call them after we have 1 million DL’s. ● Alerts: Looks like we hacked our own bank account but due to error in the code we left 23 cents. Whose code is it, i don’t care whose money.. ● Battle of API versus App developer is won by API. After all: iPhone processing power is probably greater than our server!

Editor's Notes

  • #2: Welcome to Yallzi way of Building an Analytics Engine on MongoDB to Revolutionize Advertising. Dont put on your seatbelts but please open up your curious minds as we are about to go fast into untangling and simplifying the complex problems
  • #3: I’m Steve Bond, Founder of Yallzi, where we believe your staycation is someone elses’s perfect vacation -- and vice vera! We’re crowd-funning the internet. But more on that later. In today’s session, we’ll explore how Yallzi is building an analytics engine to power our product and create a new dimension of advertising. We’ll review how we made our decisions to herd the cats of technology, schema, architecture, analytics and more as well as how MongoDB allows us to iterate quickly -- which is critical for our bootstrapped startup. Before we get starter, Who is in the room: (ops, dev, business)?? And what about MongoDB experience level… who is just exploring…. developing;... in production… TRUE EXPERTS?... Great! this is the perfect group! let’s get started
  • #4: we’ll start with an “about” (who Yallzi is, what we do, why you’ll love us), move into our technical challenges and requirements then walk through our Journey with MongoDB… we’ll sprinkle in user stories / horror stories / what we’ve learned and more and end with plenty of time for questions / dialogue.
  • #7: I’m Steve Bond, same as from a few slides ago… I went from college bench to military then back to weird civilian life, disrupting the status quo. It is fun, pain and real. Always about discipline, focus and carefully calculated risk taking. “you need to take risk but not stupid risk” In civilian life, I’ve done Engineering, Operations and Business. I’ve both consulted for and run tiny startups, to acquired companies… to some of the largest companies in the world. I ran a tech consulting company soup to nuts. Ran DB operations for Moviefone… Ran global content management at AOL. At 24/7 I ran the global consulting practice, which was acquired by WPP -- where I became VP of Global Consulting. Most recently, I ran Software Engineering at Forbes where i led the rebuild of content management, created a mobile strategy, packaged our CMS to be sold as commercial publishing software… and made a few sales. Roughly 4 years into the Forbes adventure, my bride was asked to relocate from NY to Austin. Being the man in the relationship… this meant only one thing. I put my foot down and put it hard on.. ======================= below is if reordered Luckily… this was something we could help the world with. With a personal background in... …. …… I quickly realized, we could solve this common need for travelers and locals alike!
  • #8: I put my foot down… on the gas pedal of a u-haul truck. we loaded up the apartment on UES and moved cross country This is, in sorts, how Yallzi - /jɑːlzi/ was conceived.
  • #9: We lost our favorite NYC hangouts over 2 short nights as my bride and I drove cross country to our new life. We were foreigners as we stepped out of the truck into Austin. We didn't know how to "live like Austin locals". And worst of all… It became difficult to procrastinate and find excuses not to unpack boxes. We asked ourselves why there is no app for this- Why nobody want to crowd Fun the interent
  • #10: Turned out we weren’t the only ones looking for an app like this. An app that would allow people to explore new cities, an app that would allow people to share the cities they love, an app that would advertising work for them by breaking the barrier between consumer and vendor. Locations can be Verticals: Food & Dining, Recreation, Entertainment, Arts & Culture, Sports…
  • #11: Crowd Fun The Internet
  • #12: Travel is a huge industry. Today’s travelers travel differently than we’d seen historically. We know there is a growing interest in traveling “like locals”. We see it through preferences away from hotels and towards hostels / airbnb / homeaway… We see it through travel off beaten path (versus tourist check boxes). So why not see it in how we select our travel itineraries and interact with venues!?
  • #13: So we set out to create Yallzi and crowd fun the internet YALLZI let's you share all your favorite places with friends or the whole world. (you create purpose-based groups) YALLZI let's you explore new worlds that other Yallziers have shared. YALLZI breaks the barrier between Vendor and Consumer.
  • #15: I put together a power team of folks I’d worked with before. We had a variety of skills and experiences We focused on C, C++, Java. Had been using RDBMS for 20 years Had used MongoDB for 5 years in production for consumer facing, high-profile use cases at Forbes (analytics engine, content management, etc) Ran on Extra Dry Martinis Had proven abilities to squeeze 4 weeks of work into 7 days Gift for finding Free Data before the company behind it commercialia
  • #16: I put together a power team of folks I’d worked with before. We had a variety of skills. We focused on C, C++, Java. Had been using RDBMS for 20 years Had used MongoDB for 5 years in production for consumer facing, high-profile use cases at Forbes (analytics engine, content management, etc) Ran on Extra Dry Martinis Had proven abilities to squeeze 4 weeks of work into 7 days Gift for finding Free Data before the company behind it commercia
  • #17: I put together a power team of folks I’d worked with before. We had a variety of skills. We focused on C, C++, Java. Had been using RDBMS for 20 years Had used MongoDB for 5 years in production for consumer facing, high-profile use cases at Forbes (analytics engine, content management, etc) Ran on Extra Dry Martinis Had proven abilities to squeeze 4 weeks of work into 7 days Gift for finding Free Data before the company behind it commercia
  • #18: I put together a power team of folks I’d worked with before. We had a variety of skills. We focused on C, C++, Java. Had been using RDBMS for 20 years Had used MongoDB for 5 years in production for consumer facing, high-profile use cases at Forbes (analytics engine, content management, etc) Ran on Extra Dry Martinis Had proven abilities to squeeze 4 weeks of work into 7 days Gift for finding Free Data before the company behind it commercia
  • #19: I put together a power team of folks I’d worked with before. We had a variety of skills. We focused on C, C++, Java. Had been using RDBMS for 20 years Had used MongoDB for 5 years in production for consumer facing, high-profile use cases at Forbes (analytics engine, content management, etc) Ran on Extra Dry Martinis Had proven abilities to squeeze 4 weeks of work into 7 days Gift for finding Free Data before the company behind it commercia
  • #20: I put together a power team of folks I’d worked with before. We had a variety of skills. We focused on C, C++, Java. Had been using RDBMS for 20 years Had used MongoDB for 5 years in production for consumer facing, high-profile use cases at Forbes (analytics engine, content management, etc) Ran on Extra Dry Martinis Had proven abilities to squeeze 4 weeks of work into 7 days Gift for finding Free Data before the company behind it commercia
  • #21: I put together a power team of folks I’d worked with before. We had a variety of skills. We focused on C, C++, Java. Had been using RDBMS for 20 years Had used MongoDB for 5 years in production for consumer facing, high-profile use cases at Forbes (analytics engine, content management, etc) Ran on Extra Dry Martinis Had proven abilities to squeeze 4 weeks of work into 7 days Gift for finding Free Data before the company behind it commercia
  • #22: I put together a power team of folks I’d worked with before. We had a variety of skills. We focused on C, C++, Java. Had been using RDBMS for 20 years Had used MongoDB for 5 years in production for consumer facing, high-profile use cases at Forbes (analytics engine, content management, etc) Ran on Extra Dry Martinis Had proven abilities to squeeze 4 weeks of work into 7 days Gift for finding Free Data before the company behind it commercia
  • #23: I put together a power team of folks I’d worked with before. We had a variety of skills. We focused on C, C++, Java. Had been using RDBMS for 20 years Had used MongoDB for 5 years in production for consumer facing, high-profile use cases at Forbes (analytics engine, content management, etc) Ran on Extra Dry Martinis Had proven abilities to squeeze 4 weeks of work into 7 days Gift for finding Free Data before the company behind it commercia
  • #24: We also had a variety of requirements and could see our challenges before we even began… SUMMARY: Build and applicationa and analytics engine harvesting and using real time social choice and propensity data Challenge: FLEXIBLE. Storing and managing dynamic data with usual for any stat up constant pivots for a “ sweet spot” [INSERT Examples of data: User information, map data, venue data, etc… how does this change over time?] Challenge: SPEED. Speed of iteration We’re a startup with constantly changing business requirements. We needed a database that would allow us to iterate as quickly as needed. Ex: Our business model has changed from x to y. We required a zero barrier to implement Challenge: SCALE. Scale with our success. We are a bootstrapped startup. We needed a technology compatible with cloud deployment architectures. We couldn’t put up a large upfront investment. We needed to be able to leverage the cloud /commodity hardware and will scale with our success.
  • #26: We also had a variety of requirements and could see our challenges before we even began… SUMMARY: Build and applicationa and analytics engine harvesting and using real time social choice and propensity data Challenge: FLEXIBLE. Storing and managing dynamic data with usual for any stat up constant pivots for a “ sweet spot” [INSERT Examples of data: User information, map data, venue data, etc… how does this change over time?] Challenge: SPEED. Speed of iteration We’re a startup with constantly changing business requirements. We needed a database that would allow us to iterate as quickly as needed. Ex: Our business model has changed from x to y. We required a zero barrier to implement Challenge: SCALE. Scale with our success. We are a bootstrapped startup. We needed a technology compatible with cloud deployment architectures. We couldn’t put up a large upfront investment. We needed to be able to leverage the cloud /commodity hardware and will scale with our success.
  • #30: Indexing… story of how we learned this lesson: About 5 years ago when I lead Engineering at Forbes, we were running into slow performance. To fix, we indexed…. EVERYTHING. What happened? The application CRAWLED. < how did you learn this / who helped / what did you do >
  • #31: And now we’re going to review how the app works, we’ll see both the “sausage creation” and the user interface side by side and talk through our decisions on indexing and schema to provide the analytics required for Yallzi. small, big data where data is the engine
  • #32: And now we’re going to review how the app works, we’ll see both the “sausage creation” and the user interface side by side and talk through our decisions on indexing and schema to provide the analytics required for Yallzi. small, big data where data is the engine
  • #33: And now we’re going to review how the app works, we’ll see both the “sausage creation” and the user interface side by side and talk through our decisions on indexing and schema to provide the analytics required for Yallzi. small, big data where data is the engine
  • #34: Diving into Schema: we’ll first take a dive into “Actors”.
  • #35: One type of Actor is Consumer
  • #36: USERS User Collection is personal and private User data can be shared if desired for vanity or specific purpose( dietary reqs) Location (Dynamic) geo : latitude, longitude(geoLocation) Preferences (Historical & “Acquired”) Existing preference Bob loves bicycling followed by a beer and lives on UES... A fellow Yallzier just biked East River Greenway, followed by a beer at Pony Bar. Yallzi renders this plan to Bob. A fellow Yallzier Has Shared Interests and fellow Yalzier is a referrer Shared Bob and Sue both like Mexican, Sue loves Rosa Mexicana. Yallzi asks, Will Bob?) Sue has similar interests and is a referer Adjacent and could be “Acquired” Bob likes Ballets and Opera. Sue loves this + Broadway Show. Yallzi suggest Broadway show) Sue has similar interests and is a referrer Availability (Dynamic) time Vendors
  • #37: USERS User Collection is personal and private User data can be shared if desired for vanity or specific purpose( dietary reqs) Location (Dynamic) geo : latitude, longitude(geoLocation) Preferences (Historical & “Acquired”) Existing preference Bob loves bicycling followed by a beer and lives on UES... A fellow Yallzier just biked East River Greenway, followed by a beer at Pony Bar. Yallzi renders this plan to Bob. A fellow Yallzier Has Shared Interests and fellow Yalzier is a referrer Shared Bob and Sue both like Mexican, Sue loves Rosa Mexicana. Yallzi asks, Will Bob?) Sue has similar interests and is a referer Adjacent and could be “Acquired” Bob likes Ballets and Opera. Sue loves this + Broadway Show. Yallzi suggest Broadway show) Sue has similar interests and is a referrer Availability (Dynamic) time Vendors
  • #38: USERS User Collection is personal and private User data can be shared if desired for vanity or specific purpose( dietary reqs) Location (Dynamic) geo : latitude, longitude(geoLocation) Preferences (Historical & “Acquired”) Existing preference Bob loves bicycling followed by a beer and lives on UES... A fellow Yallzier just biked East River Greenway, followed by a beer at Pony Bar. Yallzi renders this plan to Bob. A fellow Yallzier Has Shared Interests and fellow Yalzier is a referrer Shared Bob and Sue both like Mexican, Sue loves Rosa Mexicana. Yallzi asks, Will Bob?) Sue has similar interests and is a referer Adjacent and could be “Acquired” Bob likes Ballets and Opera. Sue loves this + Broadway Show. Yallzi suggest Broadway show) Sue has similar interests and is a referrer Availability (Dynamic) time Vendors
  • #39: 2nd type of Actor is Vendors. Location: Don’t move location of restaurant Vertical: A museum will be arts&culture, a Museum will (rarely, if ever) change into a Sporting Center or Restaurant.
  • #42: 68% = 2.5G  800mb
  • #43: And now we’re going to review how the app works, we’ll see both the “sausage creation” and the user interface side by side and talk through our decisions on indexing and schema to provide the analytics required for Yallzi. small, big data where data is the engine
  • #49: we design something like Google Page Ranking meets Twitter Following model for:
  • #54: And now we’re going to review how the app works, we’ll see both the “sausage creation” and the user interface side by side and talk through our decisions on indexing and schema to provide the analytics required for Yallzi. small, big data where data is the engine
  • #59: And now we’re going to review how the app works, we’ll see both the “sausage creation” and the user interface side by side and talk through our decisions on indexing and schema to provide the analytics required for Yallzi. small, big data where data is the engine
  • #60: (we crowd-fun the internet)
  • #61: And now we’re going to review how the app works, we’ll see both the “sausage creation” and the user interface side by side and talk through our decisions on indexing and schema to provide the analytics required for Yallzi. small, big data where data is the engine
  • #62: And now we’re going to review how the app works, we’ll see both the “sausage creation” and the user interface side by side and talk through our decisions on indexing and schema to provide the analytics required for Yallzi. small, big data where data is the engine
  • #64: Metrics with mongodb we were able to go from idea to prototype in x time once we prototyped, we moved into alpha roughly 1 month later we changed our business model
  • #65: As a wrap up, we (A) reviewed who Yallzi is and what we’re trying to do, we reviewed why Yallzi selected MongoDb (initially for flexibility and scale) Selected MongoDB initially for flexibility and scale, in addition to other requirements. It provided the best of both worlds: foundation of RDBMS with innovations of NoSQL. index on article makes most sense if talkign about preferences: index preferences if talkign about location, we would index xxxx overloading any collection with indices will lead to rapid degradation of performance get one collection, identify the
  • #66: So what’s next for us?: We’re wrapping up Development for our beta launch. If you’re interested, follow us on Twitter! We’re eager to partner and stay in touch and see you next year at MongoDB World. Philosophy
  • #69: Selected MongoDB initially for flexibility and scale, in addition to other requirements. It provided the best of both worlds: foundation of RDBMS with innovations of NoSQL. With MongoDB: build collections by purpose that you can aggregate on top of do not over index