Analytics in a Day Ft. Synapse Virtual Workshop

Analytics in a Day Workshop
James McAuliffe
Cloud Solution Architect

©Microsoft Corporation
Azure
Agenda
Workshop instruction and discussion
9:00–10:00 The heart of analytics – why modernize your data warehouse?
10:00–11:00 Optimizing analytics with Azure Synapse
11:00–11:15 Insights for all with Power BI + Azure Synapse
Break for 15 min
Hands-on lab
11:30–1:00 Hands-on lab using the Azure Synapse Studio
Times are approximate and will be fluid with the class

Housekeeping
Please message Sami
with any questions,
concerns or if you need
assistance during this
workshop.
Please mute your line!
We will be applying mute.
This session will be
recorded.
If you do not want to be
recorded, please disconnect at
this time.
Links:
See chat window.
Worksheet:
See handouts.
To make presentation
larger, draw the bottom
half of screen ‘up’.

James McAuliffe,
Cloud Solution Architect
James McAuliffe is a Cloud Solution Architect with over 20 years of technology
industry experience. During this journey into data and analytics, he’s held all of the
traditional Business Intelligence Solution project roles, ranging from design and
development to complete life cycle BI implementations. He is a Microsoft Preferred
Partner Solutions expert and has worked with clients of all sizes, from local
businesses to Fortune 500 companies.
And I like old Italian cars.
linkedin.com/in/jamesmcauliffesql/

A premier Microsoft partner, CCG uses leading cloud
platforms to develop solutions and provide analytics that help
customers advance their digital strategies.
6
PARTNERSHIP SPOTLIGHT: MICROSOFT
Certifications
Gold Partner
Independent System Vendor (ISV)
and Co-Seller
AI Inner Circle Partner
Technologies
Azure Data Services
Azure Data Factory
Azure Data Lake Store
Azure Databricks
Azure Cognitive Services
Azure Machine Learning
Azure Stream Analytics
Azure Analysis Services
Azure Synapse Analytics
Power BI Platform

Offerings Overview
7
Data and
Analytics Strategy
Advanced Analytics,
Machine Learning, and AI
Data Management
and Data Governance
Enterprise Business
Intelligence
Cloud Strategy, Migration,
And Management

Why Modern Data Estate?
Why Unified Data Platform?

2.8x
more likely to report
double-digit year over
year growth with
advanced insight-driven
capabilities
91%
of global executives say
effective data and analytics
strategies are essential for
business transformation
6%
average initial increase in
profits from investments in
data and analytics. That
number increases to 9%
for investments > 5 years
Data Drives Results
Data, Analytics, And Insights Investments Produce
Tangible Benefits — Yes, They Do, 2020
Understanding Why Analytics Strategies Fall Short
for Some, but Not for Others, Harvard Business
Review, 2019
Data Driven
Companies Are
Seeing The Lift
Enterprise Data and
Analytics Strategy is
Critical For growth
Analytics Investments
Show Consistent Profit
Increase
Big data: Getting a better read on performance, McKinsey
2018
46%
of enterprises are relying
on analytics to identify and
create new revenue
streams
Analytics Are Fundamental
to Transformative
Innovation
The Global State Of Enterprise Analytics, Forbes, 2019

1 - 2020, Harvard Business Review, "The New Decision Makers: Equipping Frontline Workers for Success.“
2- 2019, Deloitte Survey: Analytics and Data-driven Culture Help Companies Outperform Business Goals in the 'Age of With’
3- 2019, Companies Are Failing in Their Efforts to Become Data-Driven
Yet…..
Only 20% of organizations are giving their
employees both the authority and the tools to make
decisions based on analytics1
67% of executives surveyed are not comfortable
accessing or using data from their existing tools and
resources2
53% state that they are not yet treating data as a
business asset3
Organizations are still struggling
with successfully implementing
the meaningful transformation
necessary to become truly data-
driven.

Data Landscape – Volume and Pressure
IDC Data Age 2025 - The Digitization of the World

Azure
The heart of analytics
Section 1
Data businesses need
data warehouses
Section 2
Data warehouses and
data lakes come together
Section 3
BI & DW come together
Section 4
The cloud for modern analytics
Section 5
A new class of analytics

Section 1
Data businesses need
data warehouses

Azure
Is the data warehouse still relevant?
What’s changed since 1988?
A 30-year-old architecture, still going strong Commerce and
technology
The data warehouse itself

Azure
Today, all businesses are data businesses
Data is the lifeblood of modern work

Azure
All data businesses need
to be analytic businesses
Without analytics data is a cost center,
not a resource

Azure
Analytic businesses need
to evolve data science
Every business has opportunities to make
analytics faster, easier, and more insightful

Azure
Store
Data Ingestion Big Data Data Warehousing
The cloud data warehouse in the data-driven business

Azure
Store

Azure
Store
Cloud data
SaaS data
On-premises data
Devices data

Azure
Store

Section 2
Data warehouses and
data lakes come together

Azure
80%
report struggling to
become mature users
of data*
55%
report data silos and
data management
difficulties as roadblocks*
* Harvard Business Review (2019), Understanding why analytics strategies fall short for some, but not for others
Analytics & AI is the #1 investment for business leaders,
however they struggle to maximize ROI

Azure
Big data
Experimentation
Fast exploration
Semi-structured
Data science
OR
Relational data
Proven security & privacy
Dependable performance
Structured
Business analytics
Data lake Data warehouse
Businesses are forced to maintain
two critical, yet independent analytics systems

Azure
It’s a challenge to integrate these areas with security
Big data
Experimentation
Fast exploration
Semi-structured
Data science
OR
Relational data
Structured
Business analytics
Securing a business-critical
environment needs enterprise-
class features such as row and
column security
Relying on views only increases the
number of artifacts to be managed

Azure
Big data
Experimentation
Fast exploration
Semi-structured
Data science
OR
Relational data
Structured
Business analytics
column security
Securing a platform used for
both experimentation and
production demands the ability
to discover sensitive data
You can’t secure what you don’t know

Azure
Big data
Experimentation
Fast exploration
Semi-structured
Data science
OR
Relational data
Structured
Business analytics
column security
Securing a platform used for
both experimentation and
production demands the ability
to discover sensitive data
You can’t secure what you don’t know
User management in an
environment with diverse use
cases requires integrated
enterprise authentication

Azure
It’s a challenge to manage these diverse workloads
Big data
Experimentation
Fast exploration
Semi-structured
Data science
OR
Relational data
Structured
Business analytics
In this mixed
environment, not
all workloads have
the same priority
Mission-critical warehouse jobs are demanding
and predictable
Exploratory analytics and data science are important
but unpredictable
Executive queries are high-profile, although rare
Azure

Azure
It’s a challenge to manage these diverse workloads
Big data
Experimentation
Fast exploration
Semi-structured
Data science
OR
Relational data
Structured
Business analytics
In this mixed
environment, not
all workloads have
the same priority
Mission-critical warehouse jobs are demanding
and predictable
Exploratory analytics and data science are important
but unpredictable
Executive queries are high-profile, although rare
Throwing multiple
clusters at these
scenarios is easy,
especially in
lightweight
scenarios, however:
Each cluster has a cost
Bringing a cluster online has a lag, which can impact
important, if rare, workloads
It takes compute to maintain large caches

Azure
It’s a challenge to build integrated lifecycle management
Big data
Experimentation
Fast exploration
Semi-structured
Data science
OR
Relational data
Structured
Business analytics
Data Scientists
need a real
data lake
Query over open file formats such as Parquet and
ORC natively without loading the data to a
proprietary cluster
Enable data science platforms and the EDW to share
a common data set

Azure
It’s a challenge to build integrated lifecycle management
Big data
Experimentation
Fast exploration
Semi-structured
Data science
OR
Relational data
Structured
Business analytics
Developers need
real development
tools
Version control
Continuous integration and deployment
Unit testing, integration testing and load testing
Data Scientists
need a real
data lake
Query over open file formats such as Parquet and
ORC natively without loading the data to a
proprietary cluster
Enable data science platforms and the EDW to share
a common data set

Azure
Azure meets these challenges,
with a single service to provide limitless analytics
Welcome to limitless
Ease of use
Fast exploration
Quick to start
Proven security
Airtight privacy
Data warehousing & big data analytics—all in one service

Azure
Section 3
Azure meets these challenges,
with a single service to provide limitless analytics

Section 3

Azure
The new economy thrives
on data literacy
Communicating with data is a
critical skill in the new economy

Azure
Users and IT must come together
in the new enterprise
Get over the IT/business divide

Azure
Governance and self-service
enhance decision-making
Governance is not about making the right decisions,
it is about making decisions the right way

Azure
The importance of data models
BI models Power BI
 Built and maintained by business users or BI developers
 Use enterprise models, departmental data, and external sources
 Focused on a single subject area, but often widely shared
Machine learning
models
Azure Synapse
Analytics
 Built and maintained by data scientists
 Mostly developed from raw sources in the data lake
 Often experimental, needing a data engineer for production use
Azure Synapse
AnalyticsEnterprise models
 Built and maintained by IT architects
 Consolidated data from many systems
 Centralized as an authoritative source for reporting and analysis

Azure
If business users are
tech-smart and data
literate, why do they
need enterprise models?
Enterprise models in the
self-service environment
Consistency
Some business processes can be built once and shared as a
corporate standard
Governance
Certain data sets need complex security and privacy controls
Efficiency
No need to repeat design, preparing, and loading or securing
Line-of-business sources
Data ingestion &
transformation
Enterprise models
Azure Synapse
Analytics
Power
BI

Azure
If enterprise models
are so important, why
do users need self-
service BI models?
BI models in the
enterprise environment
Flexibility
Some data sets are temporary, external, or ad-hoc don’t need to
be consolidated
Efficiency
Tech-smart business users have fresh and innovative ideas they
need to explore with agility
Ad-hoc, departmental and
external sources
Line-of-business sources
Data ingestion &
transformation
Power
BI
Enterprise models
Azure Synapse
Analytics
BI models

Azure
What is the role of
the data warehouse
with data science?
Data science models in the
enterprise environment
Integrating results with enterprise models
Making the results of data science easily available for business functions
Serving enterprise data for data scientists
Helps ensure consistency across diverse analyses
Power
BI
Azure Synapse
Analytics
Azure
Databricks
Enterprise models
Azure Synapse
Analytics
Data science results

Section 4
The cloud for
modern analytics

Azure
Modern businesses succeed
in the cloud
The cloud is the default environment
for new technology initiatives

Azure
Cloud security offers a
new level of protection
Businesses benefit from built-in security
found only in the cloud

Azure
A cloud analytics platform
is an economic breakthrough
Price, performance, and agility

Azure
A cloud analytics platform
is the hub for all data models
Structured, unstructured, and streaming data
integrated in a single, scalable, environment

Azure
Bring together the best of both worlds with the market-leading BI service
and the industry-leading analytics platform
BI
Power BI can analyze and visualize
massive volumes of data
Azure Synapse Analytics provides a
scalable platform to enable real-time BI
Analytics

Azure
Section 5
Power BI can analyze and
visualize massive volumes of data
provides a scalable platform
to enable real-time BI
Azure Machine Learning natively
integrates with Azure Synapse
and Power BI to democratize
AI across your business
BI Analytics Machine learning

Section 5

Azure
Azure Synapse lies at the heart of business, AI, and BI
Unified experience
Azure Synapse Studio
Integration Management Monitoring Security
Analytics runtimes
SQL
Azure Data Lake Storage
Azure Machine
Learning
On-premises data
Cloud data
SaaS data
Streaming data
Power BI

Azure
Unified experienceAzure Synapse Studio
Integration Management Monitoring SecuritySQL
Azure Machine
Learning
On-premises
data
Cloud
data
SaaS data
Streaming
data
Cloud analytics has taken a leap forward
with a unified, unmatched platform
Power BI

Limitless analytics service with
unmatched time to insight

Azure
Introducing Azure
Synapse Analytics
A limitless analytics service with unmatched
time to insight, that delivers insights from all
your data, across data warehouses and big
data analytics systems, with blazing speed
Simply put, Azure Synapse is Azure SQL Data
Warehouse evolved
We have taken the same industry leading data
warehouse and elevated it to a whole new level
of performance and capabilities

Azure
Azure Synapse
Analytics
Snowflake
Standard
Amazon
Redshift
Google
BigQuery
per byte
$33
$103
$48
…$564
94% less
TPC-H benchmark comparison
Price-performance | Lower is better
* GigaOm TPC-H benchmark report, January 2019, “GigaOm report: Data Warehouse in the Cloud Benchmark
With the best price-performance
in the business
Up to 14x faster and costs 94%
less than other cloud providers
A breakthrough in the cost of enterprise analytics

Azure
Organizations that fully harness their data outperform
Migration to the cloud for
efficient business operations
Using Azure Synapse Analytics
for predictive analytics
Data consolidation using

Azure
Cloud-scale analytics
At the core of all use cases is…Azure Synapse Analytics
Real-time
analytics
Modern data
warehousing
Advanced
analytics
“We want to analyze
data coming from
multiple sources and
in varied formats”
“We want to leverage
the analytics platform
for advanced
fraud detection”
“We’re trying to get
insights from our
devices in real time”

Azure
Store
Ingest Transform Model & serve Visualize
Modern Data Warehouse

Azure
Store

Azure
Synapse SQL
Apache Spark
for Synapse
Synapse Pipelines Synapse Studio

Azure
Query and analyze data with
T-SQL using both provisioned
and serverless models
Quickly create notebooks
with your choice of Python,
Scala, SparkSQL, and .NET for
Apache Spark
Build end-to-end workflows
for your data movement and
data processing scenarios
Execute all data tasks
with a simple UI and
unified environment
Synapse SQL
Apache Spark
for Synapse

Azure
Platform
Azure
Data Lake Storage
Common Data Model
Enterprise Security
Optimized for Analytics
Data lake integrated and Common Data
Model aware
METASTORE
SECURITY
MANAGEMENT
MONITORING
Integrated platform services
for, management, security, monitoring,
and metastore
DATA INTEGRATION
Analytics Runtimes
Integrated analytics runtimes available
provisioned and serverless
Synapse SQL offering T-SQL for batch,
streaming, and interactive processing
Synapse Spark for big data processing
with Python, Scala, R and .NET
PROVISIONED (DW) SERVERLESS
Form Factors
SQL
Languages
Python .NET Java Scala R
Multiple languages suited to different
analytics workloads
Experience Synapse Studio
SaaS developer experiences for code
free and code first
Artificial Intelligence/Machine learning/Internet of Things
Intelligent Apps Business Intelligence
Designed for analytics workloads at
any scale
Integrated analytics platform for AI, BI, and continuous intelligence

Azure
Integrated analytics platform for AI, BI, and continuous intelligence
Platform
Azure
Data Lake Storage
Common Data Model
Enterprise Security
Optimized for Analytics
METASTORE
SECURITY
MANAGEMENT
MONITORING
DATA INTEGRATION
Analytics Runtimes
PROVISIONED (DW) SERVERLESS
Form Factors
SQL
Languages
Python .NET Java Scala R
Experience Synapse Studio
Artificial Intelligence/Machine learning/Internet of Things
Intelligent Apps/Business Intelligence
Connected Services
Azure Data Catalog
Azure Data Share
Azure Databricks
Azure HDInsight
Power BI
3rd Party Integration

Azure
Synapse SQL
Apache Spark
for Synapse

Synapse Studio

Azure
Synapse Studio Overview Data
Monitor Manage
Quick-access to common
gestures, most-recently used
items, and links to tutorials
and documentation.
Explore structured and
unstructured data
Centralized view of all resource
usage and activities in the
workspace.
Configure the workspace,
pool, access to artifacts
Develop
Write code and the define
business logic of the pipeline
via notebooks, SQL scripts,
Data flows, etc.
Orchestrate
Design pipelines that that
move and transform data.
Synapse Studio is divided into Activity hubs
Hubs organize the tasks needed for building
analytics solutions

Azure
Overview hub

Azure
Overview hub
Start coding immediately
Begin with SQL scripts, notebook,
data flow, and more

Azure
Data Hub
Explore data inside the workspace
and in linked storage accounts

Azure
ADLS Gen2 Account
Container (filesystem)
Filepath
Data Hub
Explore data inside the workspace
and in linked storage accounts

Azure
Data Hub—storage accounts
Preview a sample of your data

Azure
Manage access and configure standard
POSIX ACLs on files and folders

Azure
Analyze SQL scripts or notebooks
with two simple actions
Autogenerate T-SQL or PySpark

Azure
Databases
Explore workspace databases
SQL pool
SQL serverless
Apache Spark

Azure
Develop Hub—SQL scripts
Author SQL Scripts
Execute SQL script on provisioned
SQL Pool or SQL Serverless
Publish individual SQL script or multiple
SQL scripts through Publish all feature
Support for languages and Intellisense

Azure
Develop Hub—SQL scripts
View results in table or chart form and
export results in several popular formats

Azure
Develop Hub—data flows
Data flows are a visual way of
specifying how to transform data,
providing a code-free experience

Azure
Develop Hub—Power BI
Create Power BI reports in the workspace
Provide access to published reports in
the workspace
Update reports in real time from Synapse
workspace and show on Power BI service
Visually explore and analyze data

Synapse SQL

Azure
Best-in-class price
per performance
Leader in price per performance
Price-performance is calculated by GigaOm as the TPC-H metric of cost of ownership divided by composite query.

Azure
Best-in-class price
per performance
Amazon Redshift
$0
$10
$20
$30
$40
$50
$60
$550
$600
$40
$33
$47
$54
$48
$51
$564
Price-performance @ 30TB
Lower is Better
Google BigQueryAzure Synapse Analytics Snowflake
$103
$110
$152
$80
$100
$120
$140

Azure
Best-in-class price
per performance
Price-performance @ 30TB
Lower is Better
Amazon
Redshift
Google BigQuery
Flat Rate
Azure Synapse
Analytics
Google BigQuery
Flat Rate
Snowflake
Standard
$1310
$570
$309
$206
$286
$153
$0
$100
$200
$300
$400
$500
$600
Snowflake
Standard

Benchmark
Data Warehouse in the Cloud Benchmark

Azure
Machine learning enabled DW
Native PREDICT-ion
T-SQL based experience
(interactive/batch scoring)
Interoperability with other
models built elsewhere
Scoring executed where
the data lives
--T-SQL syntax for scoring data in SQL DW
SELECT
d.*, p.Score
FROM PREDICT(MODEL = @onnx_model, DATA = dbo.mytable AS d)
WITH (Score float) AS p;
Upload
models
T-SQL Language
Data Warehouse
Data
+
Score models
Model Predictions
=
Synapse SQL
Create models

Azure
Heterogenous data preparation
and ingestion
Native SQL streaming
High throughput ingestion
(up to 200MB/sec)
Delivery latencies in seconds
Ingestion throughput scales
with compute scale
Analytics capabilities
Event Hubs
IoT Hub
T-SQL language
Built-in streaming ingestion & analytics
Streaming Ingestion Data Warehouse
Synapse SQL

Azure
Empower more users
per data warehouse
Leverage up to 128 concurrent
slots, simultaneously, on a single
data warehouse
Number of simultaneous
workloads increases with
data warehouse capacity
Utilize preset functions to allocate
resources that need them the most

Azure
Workload aware
query execution
Workload isolation
Multiple workloads share
deployed resources
Reservation or shared
resource configuration
Online changes to workload policies
Intra cluster workload isolation
(Scale in)
Marketing
CREATE WORKLOAD GROUP Sales
WITH
(
[ MIN_PERCENTAGE_RESOURCE = 60 ]
[ CAP_PERCENTAGE_RESOURCE = 100 ]
[ MAX_CONCURRENCY = 6 ] )
40%
Data
warehouse
Local In-Memory + SSD Cache
Compute
1000c DWU
60%
Sales
60%
100%

Azure
See more by scaling
to petabytes
CREATE MATERIALZIED VIEW vw_ProductSales
WITH (DISTRIBUTION = HASH(ProductKey))
AS
SELECT
ProductName
ProductKey,
SUM(Amount) AS TotalSales
FROM
FactSales fs
INNER JOIN DimProduct dp ON fs.prodkey = dp.prodkey
GROUP BY
ProductName,
ProductKey

Azure
See more by scaling
to petabytes
ProductName ProductKey TotalSales
Product A 5453 784,943.00
Product B 763 48,723.00
… … …
FactSales
Table
10B Records
DimProduct
Table
1,000 Records
Materialized View
(1000 Records)
FactInventory
Table
mvw_ProductSales
1,000 Records
CREATE MATERIALZIED VIEW
mvw_ProductSales
WITH (DISTRIBUTION = HASH(ProductKey))
AS
SELECT
ProductName
ProductKey,
FROM
FactSales fs
INNER JOIN DimProduct dp
ON fs.prodkey = dp.prodkey
GROUP BY
ProductName,
ProductKey
SELECT
<COLUMNS>
FROM FactSales fs
INNER JOIN
SELECT
ProductName
ProductKey,
FROM
FactSales fs
INNER JOIN DimProduct dp
GROUP BY
ProductName,
ProductKey ) ps
INNER JOIN FactInventory
GROUP BY …

Azure
Build confidence in your
data with result set cache
Execution 2
Cache Hit
~.2 seconds
Execution 1
Cache Miss
Regular
Execution
SELECT
ProductName
ProductKey,
FROM
Fact Sales
INNER JOIN DimProduct
GROUP BY
ProductName,
ProductKey
Data
Warehouse
Resultset
Cache

Azure
Most secure data
warehouse in the cloud
Multiple levels of security between the
user and the data warehouse
...at no additional cost
Threat Protection
Network Security
Authentication
Access Control
Data Protection
Customer Data

Azure
Comprehensive security
Category Feature
Data protection
Data in transit
Data encryption at rest
Data discovery and classification
Access control
Object level security (tables/views)
Row level security
Column level security
Dynamic data masking
SQL login
Authentication Azure active directory
Multi-factor authentication
Virtual networks
Network security Firewall
Azure ExpressRoute
Threat detection
Threat protection Auditing
Vulnerability assessment

Synapse SQL (serverless)

Azure
Synapse SQL serverless scenarios
Discovery and
exploration
What’s in this file? How many rows are there? What’s the max value?
SQL serverless reduces data lake exploration to the right-click
Data
transformation
How to convert CSVs to Parquet quickly? How to transform the raw data?
Use the full power of T-SQL to transform the data in the data lake

Azure
SQL Serverless
Overview
An interactive query service that provides T-SQL
queries over high scale data in Azure Storage
Benefits
Serverless
No infrastructure
Pay only for query execution
No ETL
Offers security
Data integration with Databricks, HDInsight
T-SQL syntax to query data
Supports data in various formats
(Parquet, CSV, JSON)
Support for BI ecosystem
Azure Storage
SQL
Serverless
Query
Power BI
Azure Data
Studio
SSMS
DW
Read and write
data files
Curate and
transform data
Sync table
definitions
Read and write
data files
Azure Synapse Analytics > SQL > SQL serverless

Apache Spark for Synapse

Azure
Quickly create and
configure notebooks
Allows multiple languages in one notebook
%%<Name of language>
Offers use of temporary tables across languages
Support for syntax highlight, syntax error, syntax
code completion, smart indent, and code folding
Export results

Azure
Quickly create and
configure notebooks
As notebook cells run, the underlying
Apache Spark application status is shown,
providing immediate feedback and
progress tracking

Synapse Pipelines

Azure
90+ pre-built connectors for data integration
Overview
Linked services defines the connection
information needed for pipelines to connect
to external resources
Benefits
Offers 90+ pre-built connectors
Allows easy cross platform data migration
Represents data store or compute resources

Azure
Prep and transform data
Wrangling dataflow
Code free data preparation at scale
Mapping dataflow
Code free data transformation at scale

Azure
Data flow capabilities
Handle upserts,
updates, deletes
on SQL sinks
Add new partition
methods
Add schema
drift support
Add file handling (move
files after read, write files
to file names described
in rows, etc.)
New inventory of
functions (e.g., Hash
functions for row
comparison)
Commonly used ETL
patterns (Sequence
generator/Lookup
transformation/SCD…)
Data lineage – Capturing
sink column lineage
and impact analysis
(invaluable if this is for
enterprise deployment)
Implement commonly
used ETL patterns as
templates (SCD type1,
type2, data vault)

Insights for all with
Power BI + Azure
Power up your BI with Azure Synapse

2020 Gartner Magic Quadrant for Analytics and Business Intelligence Platforms

Azure
Where do you find yourself on the curve?
Hindsight Insight Foresight
Value
Difficulty
What happened?
Descriptive analysis
Why did it happen?
Diagnostic analysis
What will happen?
Predictive analysis
How can we make it happen?
Prescriptive analysis

Azure
Where do you find yourself on the curve?
Value
Difficulty
What happened?
Why did it happen?
Diagnostic analysis
What will happen?
Predictive analysis
BI

Azure
BI + Analytics unlock the door to AI, machine learning,
and real-time insights
Value
Difficulty
What happened?
Why did it happen?
Diagnostic analysis
What will happen?
Predictive analysis
AnalyticsBI

Azure
Power BI can analyze and
visualize massive volumes of data
provides a scalable platform
to enable real-time BI
Azure Machine Learning natively
integrates with Azure Synapse
and Power BI to democratize
AI across your business
BI Analytics Machine learning

Azure
Accelerate business value with a powerful analytics platform
Business analysts IT professionals Data scientists
Frictionless
collaboration
Unified
analytics platform
Advanced analytics
and AI
Powerful visualization
and reporting
Unmatched
capabilities
Business value
Common Data Model on Azure Data Lake StorageUnified data
Azure Synapse AnalyticsPower BI
Powerful and
integrated
tooling

Azure
Accelerate business value with a powerful analytics platform
Visualize and
report
Power BI
Model & serve
Azure Synapse
Analytics
CDM folders
Azure Data Lake
Storage
Respond instantly
Enable instant response times with
Power BI Aggregations on massive
datasets when querying at the
aggregated level
Get granular with your data
Queries at the granular level are
sent to Azure Synapse Analytics
with DirectQuery leveraging its
industry-leading performance
Save money with
industry-leading performance
Azure Synapse Analytics is up to
14x faster and 94% cheaper than
other cloud providers
View reports with a single pane
of glass
Skip the configuration when
connecting to Power BI with
integrated Power BI-authoring
directly in the Azure Synapse Studio

Azure
Customers using Azure Synapse and Power BI today
are transforming their business with purpose
27%
Faster time
to insights
271% average ROI
26%
Lower total cost
of ownership
60%
Increased customer
satisfaction
* Forrester, October 2019, “The Total Economic Impact of Microsoft Azure Analytics with Power BI”

Build Power BI dashboards
directly from Azure Synapse
Azure Synapse + Power BI integration

Azure
Azure Synapse + Power BI
View published reports in Power BI workspace

Azure
Edit reports in Synapse workspace

Azure
Real-time publish on save

Hands-on lab
Build an end-to-end analytics
solution in the Azure Synapse Studio

Azure
Lab Contents Overview

Azure
Get started today
Create a free Azure account and get started with Azure Synapse Analytics:
https://azure.microsoft.com/en-us/free/synapse-analytics/
Get in touch with us:
https://info.microsoft.com/ww-landing-contact-me-azure-analytics.html
Attend a virtual Azure Analytics workshop with Informatica:
https://now.informatica.com/Microsoft_CDW_Workshops.html#fbid=uqwtl_SXNFV
Learn more:
https://aka.ms/synapse

Azure Credits for AID attendees
Enable attendees to do continue their learning after the workshop
Starting Oct 18th, 2020, Analytics in a Day workshop (in-person or virtual) attendees get
access to another Azure lab environment(Different from the lab environment used during
workshop) to continue their learning and exploration for up to 6 hours after the workshop.
1. Attendees will get an invite email from noreply@cloudlabs.ai to activate the lab
environment to explore further. Once attendee activate the lab environment, it’ll be valid for
6 hours duration and auto-delete after that.
2. When attendee click on launch lab from invite email to activate the lab environment,
deployment could take around 45 minutes to get ready.
3. In case of any issue, attendees can reach out to CloudLabs Support team at cloudlabs-
support@spektrasystems.com . You may want to reference Analytics in a Day event from
November 17 hosted by CCG Analytics, led by James McAuliffe.
This is a limited time offer, subject to available funding.
Azure Environment Duration: 6 hours per pax. Timer will start after attendee activate the lab
environment.
Lab environment Activation Validity: 7 days from the date of workshop. Once activated, Lab
environment will be valid for 6 hours duration and auto-delete after that.

Analytics in a Day
Thank You!
James McAuliffe
jmcauliffe@ccganalytics.com
https://www.linkedin.com/in/jamesmcauliffesql/
https://ccganalytics.com/

Analytics in a Day Ft. Synapse Virtual Workshop

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