This document discusses designing big data analytics solutions on Azure. It provides an overview of Azure's data landscape and common architectural patterns and scenarios for building analytics solutions using various Azure data and analytics services. These include Azure SQL Data Warehouse, Azure Data Lake Store, Azure Data Factory, Azure Machine Learning, and Power BI for reporting and visualization. The document also discusses using these services to build solutions for scenarios like data warehousing, data lakes, ETL/ELT, machine learning, streaming analytics and more.

1. Designing Big Data Analytics
Solutions on Azure
Mohamed Tawfik
Cloud Solutions Architect
Azure CoE - EMEA

3. The 4 Industrial Revolutions (by Christoph Roser at AllAboutLean.com)

5. Azure Data Landscape

6. Source: Mastering Azure Analytics, 1st Edition - Zoiner
Tejada, O'Reilly Media, Inc., April 2017

7. Architecting Big Data Solutions on Azure:
Custom Scenarios & Patterns

8. AZURE SQL DATA WAREHOUSE
AZURE SQL DATABASE
DATA MIGRATION SERVICE
DATA MIGRATION SERVICE
DATA MIGRATION SERVICE
DATA MIGRATION SERVICE
AZURE ANALYSIS SERVICES
BUSINESS APPS
CUSTOM APPS
CUSTOM APPS
BUSINESS APPS
ANALYTICAL DASHBOARDS
Scenario 1

9. SQL Data Warehouse
An illustration
Relational Data
. . . Blobs, Azure
Data Lake Store
Binary
Data
10001110110101111011
1101010101010111100
000101010101010110
0000111100111
Poly
Base
Clients
Excel
Power
BI
Tableau
. . .
Transact-SQL Query
. . .ComputeComputeCompute

10. AZURE CLI, AZURE DATA FACTORY
DATA MIGRATION SERVICE
AZURE SQL DATA WAREHOUSE ANALYTICAL DASHBOARDSAZURE ANALYSIS SERVICES
Scenario 2

11. New Pipeline Model
Rich pipeline orchestration
Triggers – ondemand, schedule, event
Data Movement as a
Service
Cloud, Hybrid
30 connectors provided
SSIS Package Execution
In a managed cloud environment
Use familiar tools, SSMS & SSDT
Author & Monitor
Programmability (Python, .NET, Powershell, etc)
Visual Tools (coming soon)
Stored Procedures
Hadoop on Azure
Trusted data
BI & analyticsData Lake Analytics
Custom Code
Machine Learning

12. Category Data store Supported as source Supported as sink
Azure
Azure Data Lake Store
Azure Blob storage
Azure SQL Database
Azure SQL Data Warehouse
Azure Table storage
Azure DocumentDB
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
Databases
SQL Server*
Oracle*
MySQL*
DB2*
Teradata*
PostgreSQL*
Sybase*
Cassandra*
MongoDB*
Amazon Redshift
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
File
File System*
HDFS*
Amazon S3
✓
✓
✓
✓
Others
Salesforce
Generic ODBC*
Generic OData
Web Table (table from HTML)
GE Historian*
✓
✓
✓
✓
✓

14. AZURE CLI, AZURE DATA FACTORY
DATA MIGRATION SERVICE
AZURE SQL DATA WAREHOUSE ANALYTICAL DASHBOARDSAZURE ANALYSIS SERVICES
ExpressRoute
Scenario 3

15. AZURE STORAGE
Polybase
ANALYTICAL DASHBOARDS
AZURE SQL DATA WAREHOUSE
DATA FACTORY
DATA FACTORY
AZURE FUNCTIONS
Scenario 4

16. ANALYTICAL DASHBOARDS
AZURE SQL DATA WAREHOUSE
DATA FACTORY
DATA FACTORY
AZURE DATA LAKE STORE
Scenario 5
AZURE FUNCTIONS

17. No limits to SCALE
Store ANY DATA in its native format
HADOOP FILE SYSTEM (HDFS) for the
cloud
Optimized for analytics workload
PERFORMANCE
ENTERPRISE GRADE access control,
encryption at rest
A hyper scale repository for big
data analytics workloads

18. Map reduce
HBase
transactions
Any HDFS applicationHive query
Azure HDInsight
Hadoop WebHDFS client
Azure Data Lake Store
WebHDFS-compatible REST API
Spark queries

19. Enterprise grade security

20. ADL .NET SDK
ADL
PowerShell
ADL
XPlat CLI
ADL Node.js SDK ADL Java SDK ADL Python*
Your application
Azure and ADL Store REST APIs

21. Capability ADLS Azure Blob
Purpose Optimized for Analytics
Analysis using Batch, Interactive, Streaming, ML
General purpose storage scenarios
App backend, backup data, media storage for
streaming, log files, IoT telemetry, Big Data
analytics
Geographic Availability East US 2, Central US, North Europe All Data Centers
HDFS Yes (Web HDFS) No
Scale No Limit on Bandwidth or Storage size Limits
-5PB Storage (announced)
-50GBps Bandwidth
Authentication & Authorization Azure Active Directory
POSIX ACLs on Files and Folders
Access keys & SAS tokens
Structure Accounts / Folders / Files (with Hierarchical
folders)
Accounts / Containers / Blobs (flat namespace)
Encryption Yes Yes
Geo- Replication No Yes [LRS, GRS, RA-GRS]
Cost [1PB] $40K
Coming soon
HOT $20K
COOL $16K

22. LOB
Applications
SocialDevices
Clickstream
Sensors
Video
Web
Relational
A highly scalable, distributed, parallel file system in the cloud specifically designed to work
with a variety of big data analytics workloads
Azure Data Lake Store
Batch
Map
Reduce
Script
Pig
SQL
Hive
NoSQL
HBase
In-Memory
Spark
Predictive
R Server
Batch
U-SQL
HDInsight
ADL
Analytics

23. ANALYTICAL DASHBOARDS
AZURE SQL DATA WAREHOUSE
DATA FACTORY
DATA FACTORY
AZURE DATA LAKE STORE
Scenario 6

24. Azure Batch
Enable applications and algorithms
to easily and efficiently run in
parallel at scale
Rendering
Media transcoding & pre-/post-
processing
Test execution
Monte Carlo simulations
Genomics
Deep Learning
OCR
Data ingestion, processing, ETL
R at scale
Compiled MATLAB
Engineering simulations
Image analysis & processing

25. INPUT OUTPUT
Azure Batch
Concepts
Applications /
Algorithms
Queue
Pool of VMs
Jobs &
Tasks

26. Azure Batch Rendering GA
Queue
Upload assets
Submit job
Return outputs
Pay-per-minute
licensing
Windows and Linux VMs
Autodesk Maya
Plug-in
Batch Labs
x-plat client
Azure CLI /
PowerShell APIs
Monitor job

27. ANALYTICAL DASHBOARDS
AZURE SQL DATA WAREHOUSE
DATA FACTORY
DATA FACTORY
AZURE DATA LAKE STORE AZURE DATA LAKE ANALYTICS
Scenario 7

28. Data Lake Analytics Workloads
With BATCH workload, Data Lake Analytics is ideal for
• The transformation and preparation of data for use in other systems
• Analytics on VERY LARGE amounts of data
• Massively Parallel programs written in .NET, Python and R, scaled out with U-
SQL
• Performing Cognition at Scale on large collections

29. Data Lake Analytics
Data Lake Store
An illustration
U-SQL Query
. . .ComputeComputeCompute
Unstructured Data
. . .

30. U-SQL
Query
Query
Azure
Storage Blobs
Azure SQL
in VMs
Azure
SQL DB
Azure Data
Lake Analytics
Azure
SQL Data Warehouse
Azure
Data Lake Storage
Easily query data in multiple Azure data stores
without moving it to a single store

31. Embedded Artificial Intelligence
Host Deep Neural Networks (DNNs)
6 Built-in Cognitive Functions
– Face API
– Image Tagging
– Emotion analysis
– OCR
– Text Key Phrase Extraction
– Text Sentiment Analysis

32. Extract
Process
Output
User CodeUser Code
User Code
User Code
Declarative Framework
User Extensions
U-SQL Example
Extract
User Code
User Code

33. U-SQL
Declarative
+
Imperative
Structured
+
Semi-structured
+
Unstructured
Batch
+
Interactive
+
Streaming
+
Machine Learning
Programming models Data Workloads
a language that unifies

34. ANALYTICAL DASHBOARDS
AZURE SQL DATA WAREHOUSE
DATA FACTORY
DATA FACTORY
AZURE DATA LAKE STORE AZURE DATA LAKE ANALYTICS
Scenario 8
AZURE DATA LAKE ANALYTICS
Cleansing Analysis

35. Orchestration Key ManagementPrivate Connections Monitoring
AZURE EXPRESSROUTE AZURE DATA FACTORY AZURE KEY VAULT OPERATIONS MANAGEMENT SUITE
ANALYTICAL DASHBOARDS
AZURE SQL DATA WAREHOUSE
DATA FACTORY
DATA FACTORY
AZURE DATA LAKE STORE AZURE DATA LAKE ANALYTICS WEB & MOBILE APPS
AZURE STREAM ANALYTICS
Scenario 9
Azure Time Series Insights

36. Store and manage terabytes of time-series data
Explore and visualize billions of events simultaneously
Conduct root-cause analysis, and to compare multiple sites and assets

37. Illustrating an application
Stream Analytics
Time
Window
SELECT …
Written in Stream Analytics
Query Language, a subset
of T-SQL
Stream
A standing
query

38. Orchestration Key ManagementPrivate Connections Monitoring
AZURE EXPRESSROUTE AZURE DATA FACTORY AZURE KEY VAULT OPERATIONS MANAGEMENT SUITE
ANALYTICAL DASHBOARDS
AZURE SQL DATA WAREHOUSE
DATA FACTORY
DATA FACTORY
AZURE DATA LAKE STORE AZURE DATA LAKE ANALYTICS COSMOS DB WEB & MOBILE APPS
AZURE STREAM ANALYTICS
Scenario 10

40. Orchestration Key ManagementPrivate Connections Monitoring
AZURE EXPRESSROUTE AZURE DATA FACTORY AZURE KEY VAULT OPERATIONS MANAGEMENT SUITE
ANALYTICAL DASHBOARDS
AZURE SQL DATA WAREHOUSE
DATA FACTORY
DATA FACTORY
AZURE MACHINE LEARNING & MACHINE LEARNING SERVER
AZURE DATA LAKE STORE AZURE DATA LAKE ANALYTICS COSMOS DB WEB & MOBILE APPS
AZURE STREAM ANALYTICS
Scenario 11

41. $2,600.45
$2,294.58
$1,003.30
$8,488.32
Name Amount Fraudulent
Smith
Janet
John
Adams
No
Yes
Yes
No
What’s the pattern for
fraudulent
transactions?

42. $2,600.45
$2,294.58
$1,003.30
$8,488.32
Name Amount Fraudulent
Smith
Janet
John
Adams
No
Yes
Yes
No
Where
Issued
Where
Used
Age of
Cardholder
$200.12
$3,250.11
$8,156.20
$7,475.11
Pali
Jones
Hanford
Marx
USA
USA
USA
FRA
AUS
USA
USA
UK
22
29
25
64
58
43
27
32
No
No
Yes
No
USA
RUS
RUS
USA
JAP
RUS
RUS
GER
$540.00
$7,475.11
Norse
Edson
USA
USA
27
20
No
Yes
RUS
RUS
What’s the pattern
for fraudulent
transactions?

43. Illustrating the process

44. MICROSOFTAZURE
Model
Call Center Staff
Call Center
ApplicationBlobsDetailed
Call Data
ONPREMISES
CRM
Data
Data
for ML
Aggregated
Call Data
ADLA Azure ML
Azure Data Factory
Need a real-time
prediction of each caller’s
propensity to churn
Model is rebuil
and redeployed
regularly

45. Orchestration Key ManagementPrivate Connections Monitoring
AZURE EXPRESSROUTE AZURE DATA FACTORY AZURE KEY VAULT OPERATIONS MANAGEMENT SUITE
AZURE SQL DATA WAREHOUSE
DATA FACTORY
DATA FACTORY
AZURE MACHINE LEARNING & MACHINE LEARNING SERVER
AZURE DATA LAKE STORE AZURE DATA LAKE ANALYTICS COSMOS DB WEB & MOBILE APPS
AZURE STREAM ANALYTICS
Scenario 12
Power BI
Power BI
Embedded

46. http://bit.ly/pbie

47. Microsoft Azure
subscription
Embed
End users
Workspace
Workspace collection
1,N
Developer
Name
Admin Users
Endpoints
Keys
Gateways
Credentials
Geo Location
Tags
Name
Reports
Datasets
Tags
Your app
Azure SQL
Data Warehouse
Azure SQL Database
1,N
1,N

48. Power BI
Users
Permissions
Auth. providers
API keys
Token
+ Claim: Can view Report 1
+ Expiration: 5 minutes
User requests to view
Report 1
Validate token
API keys
Report 2
Workspace
Report 1
Application
Provide seamless authentication experiences

49. Provide seamless authentication experiences
Power BI
Users
Permissions
Auth. providers
API keys API keys
Report 2
Workspace
Report 1Report 1
Application

50. Row Level Security

51. Users
Application
Permissions
Auth. providers
Power BI
API keys
Report 2
Workspace
Report 1
Token
+ Claim: Can view Report 1
+ Expiration: 5 minutes
+ username: “user1”
+ roles: “sales”
API keys
Copy API keys to your application
Sign token
Provide seamless authentication experiences

52. Power BI REST API
Authentication flow: Web application

54. FAQ
• What is a report session and how is it billed?
• A session is a set of interactions between an end user and a Power BI Embedded report.
Each time a Power BI Embedded report is displayed to a user, a session is initiated and the
subscription holder will be charged for a session. Sessions are billed at a flat rate,
independent of the number of visual elements in a report or how frequently the report
content is refreshed. A session ends when either the user closes the report, or the session
times out after one hour.
• Do you offer any tools or guidance to help me estimate how many renders/session I
should expect? How will I know how many renders have been completed?
• The Azure Portal will provide billing details on how many renders / report sessions have
been performed against your subscription.
• Do I need a Power BI subscription in order to develop applications with Power BI
Embedded? How do I get started?
• As the application developer, you do not need to have a Power BI subscription in order to
create the reports and visualizations you wish to use in your application. You will need a
Microsoft Azure subscription and the free Power BI Desktop application.

55. Orchestration Key ManagementPrivate Connections Monitoring
AZURE EXPRESSROUTE AZURE DATA FACTORY AZURE KEY VAULT OPERATIONS MANAGEMENT SUITE
AZURE SQL DATA WAREHOUSE
DATA FACTORY
DATA FACTORY
AZURE MACHINE LEARNING & MACHINE LEARNING SERVER
AZURE DATA LAKE STORE AZURE DATA LAKE ANALYTICS COSMOS DB WEB & MOBILE APPS
AZURE STREAM ANALYTICS
Scenario 13
Power BI
COGNITIVE SERVICESBOT SERVICE Logic App

56. Orchestration Key ManagementPrivate Connections Monitoring
AZURE EXPRESSROUTE AZURE DATA FACTORY AZURE KEY VAULT OPERATIONS MANAGEMENT SUITE
AZURE SQL DATA WAREHOUSE
DATA FACTORY
DATA FACTORY
AZURE MACHINE LEARNING & MACHINE LEARNING SERVER
AZURE DATA LAKE STORE WEB & MOBILE APPS
Scenario 14
ANALYTICAL DASHBOARDS
AZURE HDINSIGHT
(Hadoop/Hive)
AZURE HDINSIGHT
(Hadoop/Storm)
AZURE HDINSIGHT
(Hadoop/Kafka)
Kafka
AZURE HDINSIGHT
(Hadoop/HBase)
COGNITIVE SERVICESBOT SERVICE Logic App

57. Clusters
Microsoft Azure Datacenter
HDInsight Cluster
VMVMVMVMVMVMVMVMVMVMVMVM
Created through the
Azure portal

59. Microsoft Hadoop Stack
Azure HDInsight
Machine
Learning
Local (HDFS) or Cloud (Azure Blob/Azure Data Lake Store)

60. Open source analytics
service for the Enterprise

61. Multi Region Availability
Available in >25 regions world-wide
Launched most recently in US West 2, and UK
regions
Available in China, Europe and US
Government clouds

62. IaaS Clusters Managed Clusters Big Data as-a-service
Best for…
Workloads
Administrative
Developer
Control &
configuration
Service Level
Agreement
TCO
CONTROL EASE OF USE AND ADOPTION

63. Orchestration Key ManagementPrivate Connections Monitoring
AZURE EXPRESSROUTE AZURE DATA FACTORY AZURE KEY VAULT OPERATIONS MANAGEMENT SUITE
AZURE SQL DATA WAREHOUSE
DATA FACTORY
DATA FACTORY
AZURE DATA LAKE STORE
Scenario 14
ANALYTICAL DASHBOARDS
AZURE HDINSIGHT
(Hadoop/Hive)
AZURE HDINSIGHT
(Hadoop/Storm)
AZURE HDINSIGHT
(Hadoop/Kafka)
Kafka
AZURE HDINSIGHT
(Hadoop/R)
Jupyter
Data Science
Notebooks
AZURE HDINSIGHT
(Hadoop/Spark)

64. Community Algorithms
Spark ML (PySpark, SparkR)
Caffe on Spark
BigDL on HDInsight
SparklyR
XGBoost
Supported by community
ISV Applications
H2O
Dataiku
Supported by ISV

66. Orchestration Key ManagementPrivate Connections Monitoring
AZURE EXPRESSROUTE AZURE DATA FACTORY AZURE KEY VAULT OPERATIONS MANAGEMENT SUITE
AZURE SQL DATA WAREHOUSE
DATA FACTORY
DATA FACTORY
AZURE DATA LAKE STORE
Scenario 15
ANALYTICAL DASHBOARDS
AZURE HDINSIGHT
(Hadoop/Hive)
AZURE HDINSIGHT
(Hadoop/Storm)
AZURE HDINSIGHT
(Hadoop/Kafka)
Kafka
AZURE HDINSIGHT
(Hadoop/R)
Jupyter
Data Science
Notebooks
AZURE HDINSIGHT
(Hadoop/Spark)
DATA CATALOG

67. Analyze
Enabling the Entire Enterprise Data Ecosystem
• Search
• Browse
• Filter
Discover
• Metadata
• Experts
• Context
Understand
• Your data
• Your tools
• Your way
Consume
• Tag
• Document
• Publish
Contribute

71. Source: Mastering Azure Analytics, 1st Edition - Zoiner
Tejada, O'Reilly Media, Inc., April 2017

72. Thank You
Mohamed Tawfik
Cloud Solutions Architect
Azure CoE - EMEA