Monetizing Big Data with Streaming Analytics for Telecoms Service Providers

MONETIZING BIG DATA with
STREAMING ANALYTICS!
For Communications Service Providers and the
Telecoms Industry
Copyright
©
2014
–
Proprietary
and
Confiden7al
Informa7on
of
SQLstream
Inc.

SCOPE
§ Explain real-time Big Data and streaming analytics
§ Explore real-time applications in the Telecoms industry
§ Share our thoughts, experience and use cases
2Copyright © 2014 – Proprietary and Confidential Information of SQLstream Inc.

Today’s Presenter
Ronnie
Beggs
Vice
President
Marke3ng
&
Product
Management,
SQLstream
§ Over
twenty
years
experience
of
product
management,
marke7ng
and
business
development
in
the
real-‐7me
soKware
business.
§ Worked
for
a
number
of
successful
start-‐ups,
from
early
stage
through
to
acquisi7on,
including
Metrica
(ADC)
and
Cramer
Systems
(Amdocs).

About SQLstream
Distributed
stream
processing
plaYorm
for
opera7onal
intelligence
and
the
Internet
of
Things,
delivering
streaming
analy7cs
and
real-‐7me
ac7ons
facts
§ Launched
2009
from
log
and
sensor
machine
data.
§ Worldwide
customer
base
across
mul7ple
industries
§ Strategic
partnerships
for
opera7onal
intelligence
(logs)
and
Internet
of
Things
(sensors)
capabili7es
§ Process
unstructured
and
structured
machine
data
§ Accelerate
and
extend
Hadoop
&
RDBMS
§ Open,
standards-‐based
plaYorm
based
on
SQL
differen7ators
§ Massively
scalable
streaming
data
plaYorm
§ Only
true
standard
SQL
streaming
engine
§ Covered
by
7
broad
patents
for
stream
processing

What’s happening with Big Data?
§ Stored information doubling every 18-24 months
§ “Internet of Things” is creating new data with no human
interaction
§ Business decisions need to happen faster based on real-time,
actionable intelligence
§ Streaming and predictive analytics are changing the way
we interact with our operational systems and customers.

Looking Forward with Streaming Analytics
§ Enterprises have been managed based on prior history delivered at
the end of the day, month or quarter.
§ Streaming analytics enables
enterprises to drive their
business in real-time, reacting
to changes and opportunities
as they happen.

Telecoms and Big Data
$5.4B
Communica7ons
analy7cs
market
by
2019.
Market
Research
Report.biz
AREAS OF NEEDS
§ Customer Experience
§ Fraud prevention
§ IP Network & Service Performance
§ Call Center Experience
Streaming Value
Improved
opera7onal
efficiency
and
customer
sa7sfac7on,
with
a
real-‐7me
360o
customer
view,
and
con7nuous
data
silo
integra7on
Call
Centers|
Telecommunica7ons
|
Data
Centers
ISSUES
§ Untapped New (Big) Data
§ Ease of churn
§ Lacking a 360o customer view

Streaming Analytics as a Complement to Traditional Data
Management
Repeated
Queries
DATABASE
Collect,
translate,
classify
DATA
ANALYSIS
PATTERN
DETECTION
ACTION
TIME
STREAMING
DATA
ANALYTICS
PLATFORM
DATA
Ac7on
Ac7on
C-‐ETL
Aggrega7on
Classifica7on
Profiling
Deep
analy7cs
Trend
detec7on
Trend
correla7on
Extrapola7on
Alerts
Ac7ons
Seconds
Hours
-‐>
Days
DATA
DATA

OPERATIONAL INTELLIGENCE
Integrating Operations and Analytics in Real-time
Real-time Operational Intelligence
Business
Intelligence
As we move toward a real-time business environment, the capability to process data flows
swiftly and flexibly will become increasingly important. SQLstream leads the industry in
this kind of capability. ” Robin Bloor
Chief Analyst for Bloor Group
Operations
Continuous monitoring and analytics
Improve decision-making
Automate operational processes
Billing
Rating
QoE
Network analysis
Fraud Monitoring
”

The Information Value Chain
What is happening?
What might happen?
What just happened?
Make stuff happen!

Actionable insights - the ideal scenario
SOURCESSYSTEMS & APPS
Alerts
ENTERPRISE
§ Operations
§ Customer Care
§ Marketing
§ Logistics
MACHINE DATA
§ Unstructured
§ Semi-structured
§ Structured
§ Log, sensor & network
QoE
STREAMING
ANALYTICS
Actions
Dashboards
Continuous ETL

What’s possible from xDRs | APPLICATIONS
NETWORK
SERVICE
CUSTOMER
BUSINESS
§ Op7miza7on
of
network
u7liza7on
§ Network
Capacity
planning
§ Anomaly
detec7on
&
troubleshoo7ng
§ Monitoring
and
protec7on
§ Self-‐healing
networks
§ Partner
rou7ng
§ Subscriber
profiling
and
informa7on
§ New
product
rollout
visibility
§ Product
development
and
tariff
op7miza7on
§ Yield
management
and
dynamic
pricing
§ Service
personaliza7on
§ Customer
loyalty
management
§ Churn
preven7on
§ Device
analysis
§ Campaign
management
and
precision
marke7ng
§ Contact
center
alerts
§ New
customer
experience
monitoring
§ Billing
accuracy
and
revenue
§ SLA
management
§ Interconnect
billing
analysis
§ Real-‐7me
reports
§ Fraud
and
suspicious
traffic
detec7on

Data Analysis Today – far from Real Time
Current architectures
§ Multi-stage process
§ Offline ETL
§ Interim storage with no analytics capability
ETL / RDBMS process challenges
§ Volume and Velocity
§ Variable, changing formats
§ New types and formats
IMPACT
§ High Cost of Ownership
§ Delays to process the billing information
§ Delays in external distribution to partners
BI
Queries
and
Aggrega4on
Scripts
WAREHOUSES
Near-‐term
data
storage
PLATFORMS
Real-‐4me
ETL

STREAMING ANALYTICS
ARCHITECTURES

Generating Operational Intelligence | Process
Internet
of
Things
&
Sensors
§ Smart
City
§ Transporta7on
§ Industrial
Internet
§ Telema7cs
§ Smart
Energy
Opera3onal
Intelligence
&
Logs
§ Security
Intelligence
§ Servers
&
Applica7ons
§ Networks
&
Services
Streaming
Enterprise
Hadoop
and
Data
Warehouse
integra7on
for
joining
streaming
and
stored
trend
data
Machine
Data
Social
Media
&
TwiDer
Real-‐3me
Ac3ons
Real-‐3me
Dashboards
Con3nuous
Data
Warehouse
Updates
Automated
Ac3ons
Con7nuous
SQL
queries
over
live
data
streams
genera7ng
streaming
analy7cs
and
driving
real-‐7me
ac7ons

CDR and IPDR Analysis!
Where is the intelligence?
Timestamp
Transaction TRANS,2013-02-17-15:30:22,3458783,2347897953,128.56.0.253,STATUS:-15, DE69975, 4157588342
Log Details
Web Server
Logs
CDRs
Device
Locations
Twitter
Timestamp
[Sun Feb 17 15:30:49 2013] [notice] srv-sfo-08 caught SIGTERM, shutting down
[Sun Feb 17 15:30:49 2013] [notice] Apache/2.2.21 -- resuming normal operations
TERMINATE,ctl09gsx,01299796304,GMT-08:00,02-17-13,15:21:00,9,387,64ms,02-17-13,15:30:55,0005,
IP-TO-IP,4157588342,8775715775,1,0,4157588342,RD_AXY_NN0_001,SFR01AAG34,40.50.245.60,
234.234.60.75,65678,411,399,SIP,SANFRANCISCO,0x4B1698,0x0005E,0x49768,4157588342,0198873465
<id>1597831220</id><deviceid>0198873465</deviceid><lat>lat=47.643957</lat><lon>lon=
-122.3269</lon><time>2013-02-17T15:37:26Z</time><bearing>223.4535</bearing>
<id>1597865781</id><deviceid>0198873465</deviceid><lat>lat=47.645982</
lat><lon>lon=-122.327500</lon><time>2013-02-17T15:37:26Z</time><bearing>200.6138</bearing>
<id>1597940125</id><deviceid>0198873465</deviceid><lat>lat=47.647381</
lat><lon>lon=-122.326501</lon><time>2013-02-17T15:37:26Z</time><bearing>87.4357</bearing>
{"created_at:Thu Feb 17 15:30:55 +0000 2013,id:304612775055998976,id_str:
304612775055998976,text:@MyServiceProvider today sucks, keeps dropped!,source:u006ca
href=http:www.url.com rel=nofollow,followers_count:147,friends_count:10142, location: San Francisco,
time_zone: Pacific, geo_enabled:true, location:u00dcT: -6.1987552,106.8661953, screen_name:APerson
Timestamp
Timestamp
Timestamp
Customer
Mobile
#
Mobile
#
Term
Reason
Device
ID
Device
ID
Loca7on
Loca7on
Service
Provider
Fail
Code
Server

Enterprise-Class Real-time Data Hub
Stream Processing for Operational Intelligence and the Internet of Things
SQLstream
Blaze
s-Visualizer
real-time dashboards for
Enterprise Power Users
s-Server
StreamLab
Intelligent guided data stream discovery,
analytics and visualization without coding
Distributed SQL Stream
Processor
s-Dashboard
HTML5 real-time
dashboards for Developers
Storm
Adapter
s-Studio
Developer & Admin

SQLstream Blaze – Core Platform Architecture
Interac3ve
Stream
Discovery
and
Visualiza3on
Web Sockets
Stream Processing Engine
Machine
Data
Agents
Enterprise
Systems
Data Warehouse
SQL Database
Predictive Analytics
Repor3ng
Tools
JDBC
Control
Systems
SQL Optimizer
Parallel Scheduler
Real-time Indexing
RT Memory Manager
Dynamic Java Analytics (UDX)
Streaming Data Protocol
(HTML5)!
Discovery
API Connect
Remote
Systems
Agents
Enterprise
Systems
Devices
&
Apps
Native
Tables
Web
Agent
REST
(HTML5)!
Dashboards
(Flash)!
Dashboards
JDBC
Adapters
Devices
&
Apps
JDBC
Adapters
Hadoop / HDFS
HBase
Storm & Kafka
Enterprise
BI
Hadoop
&
NoSQL

StreamLab!
Intelligent guided data stream discovery and visualization in minutes
1. Connect to the data sources
3. Streaming dashboards
2. Structure, filter and format the streams
Interactive Stream Browser
Suggestions
Tool
User History

Case study: Real-time Call Fraud Prevention
Customer call profile
Alerts
Triggers
Reports
STREAMING
ANALYTICS
• Call suspension
• Acct. suspension
Destination• Email Alerts
Location
IP spoofing alerts
duration
Mo Tue Wed Thu Fri Sat Sun
① LA
② Nairobi
③ NY
④ …..
① LA
② SF
③ NY
④ ….
① LA
② Detroit
① LA
② LA1
Dashboards

Real-time Call Rating & Fraud
“SQLstream
allows
Veracity
to
provide
vital
real-‐7me
reports
to
our
customers
that
previously
took
hours
to
create.
SQLstream
also
provides
real-‐7me
monitoring
and
insight
into
network
concerns
allowing
Veracity
to
proac7vely
address
any
such
issues”
Veracity Networks
§ Internet
provider
§ Residen7al
and
business
§ Range
of
IP-‐based
services
OPPORTUNITIES
§ CDR/IPDR
real-‐7me
analy7cs
§ Real-‐7me
ra7ng
and
QoE
§ Fraud
preven7on
BENEFITS
§
Improved
customer
sa7sfac7on
§
Improved
bandwidth
u7liza7on
§
Improved
fraud
detec7on
7mes

Customer Benchmarked Performance!
Large Network & Telecom Equipment Manufacturer
SQLstream
Network Data
Network Data
Network Data
Network Data
Network Data
ENRICH
ANALYZE
SHARE
Remote
Agent
Remote
Agent
Remote
Agent
Remote
Agent
Remote
Agent
Data
Warehouse
External
Systems
External Data
PERFORMANCE STATISTICS
System Throughput:
1.35M events / sec
Server Configuration:
1 x 4-core CPU
Event Size:
~1KB
Data Sources:
Many
SYSTEM CHARACTERISTICS
Collection:
Intelligent Remote Agents (Distributed)
Enrichment:
Streaming data augmentation
Analytics:
Temporal & spatial pattern detection
Output:
Data warehouse + applications (JDBC)

Conclusions
§ Drivers for Streaming Data Analytics
§ Declining revenue streams
§ Increasing data monetization gap
§ A Big Data problem: Volume, Velocity and Variety
§ Current technology and solutions are far from real-time
§ SQLstream’s Real-time Advantage
§ Low latency correlation, alerts and actions across all data sources
§ Streaming enrichment
§ Continuous integration with existing platforms
§ Drives real-time rating, billing, QoE and QoS, and fraud

Download SQLstream Blaze for free!!
www.sqlstream.com/downloads
Contact us:
Email: inquiries@sqlstream.com
Call: +1 877-571-5775
Ronnie Beggs | ronnie.beggs@sqlstream.com | +1 415 758 8342 | @sqlstream
Copyright
©
2014
–
Proprietary
and
Confiden7al
Informa7on
of
SQLstream
Inc.
Twitter: @sqlstream
Facebook: facebook.com/user/sqlstream
LinkedIn: linkedin.com/company/sqlstream

Monetizing Big Data with Streaming Analytics for Telecoms Service Providers

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