Business Intelligence (BI) solutions need to move at the speed of business. Unfortunately, roadblocks related to availability of resources and deployment often present an issue. What if you could accelerate the deployment of an entire BI infrastructure to just a couple hours and start loading data into it by the end of the day. In this session, we'll demonstrate how to leverage Microsoft tools and the Azure cloud environment to build out a BI solution and begin providing analytics to your team with tools such as Power BI. By end of the session, you'll gain an understanding of the capabilities of Azure and how you can start building an end to end BI proof-of-concept today.

1. Accelerating Business
Intelligence Solutions
With Microsoft Azure
Jason Strate, Principal Consultant,
Pragmatic Works

2. 100 Level Session
• Concepts
• Architecture
• High level
Session Expectations
2

3. 3
Please silence
cell phones

4.  Been asked to deliver analytics on data that you lacked
the tools to accomplish?
 Cobbled together a “solution” with tools that “worked”?
 Had an idea for a reporting solution you wanted to
implement?
Have you ever…
4

5. 5
I could be
playing Destiny
right now.

6. 6
DNS
DNS
Sharepoint Sharepoint
Sharepoint Sharepoint
SQL Server SQL Server
SSAS SSAS

7. My data warehouse front
bus CPU clocking memory
thing isn’t big enough to side
swipe the IOPS eating
carpal tunnel?

8. 8
If you can dream it,
you can build it
--Walt Disney

9. 9
Let’s
democratize
data

10. Solution Overview
Why go Azure?
Azure Build
Accelerating BI Solutions
10

11. 1. Help YOU understand capabilities of
Azure
2. Show YOU how solutions can be
envisioned
3. Empower YOU to start building solutions
Goals Today
11

12. Solution
Overview
Solution
Overview
Why go
Azure?
Azure Build
12

13. You need to…
• Get some data
• Clean up some issues
• Make a prediction
• Build a report
Your Analytic Mission
13

14. Building A Solution
14
Files

15. Aviation Data Solution
FAA Air Incident Data
Files
• Afile (air incident data)
• Efile (edited remarks)
• Aidcodes (associated tables and codes)
• Aircraftseries (aircraft data, model, make)
• Airport (airports and locations)

16. Aviation Data Solution
16

17. Why go
Azure?
Solution
Overview
Why go
Azure?
Azure Build
17

18. Common BI Roadblocks
 Analysis paralysis
 Cost of platform
 Acquisition of platform
 Time to value

20. Elastic/Scale
Growth
Optimize
Investments
Maximize
Investments
Why go Azure?
20

21. • Try new capabilities
• Add resources as needed
• Reduce lead time for growth
• Scale existing resources
• Flexible deployment models
Elastic/Scale Growth

22. Self-service provisioning
• Platform as a Service
• Infrastructure as a Service
Pay as you go
• By minutestorage GB
• Disable resources
Optimize Investments

23. • Extend existing solution
• Seamless interaction
• Enhance high availability
• Provide disaster recovery
Maximize Investments

24. 24
Cloud Computing Models

25. • Provides service configuration
• Removes infrastructure concerns
• Plug and play feel for solutions
• Ideal for analytic solution delivery
Platform as a Service
25

26. Azure PaaS
Solution
Overview
Why go
Azure?
Azure Build
26

27. Building A Solution
27
Files

28. Solution Components
Storage
SQL
Database
SQL Data
Warehouse
Data
Factory
Machine
Learning
Power BI

29. Storage
Storage SQL Database SQL Data Warehouse Data Factory Machine Learning Power BI

30. High scale, low-cost storage option
• SQL Database backups
• Data files (csv, txt, etc)
• Images and videos
Online accessible storage location
• Private
• Public
Storage

31. Create Azure Storage
31

32. Download Azure SDK 2.7
Load Data to Azure Storage

33. Azure
Storage Demo
33

34. SQL Database
Storage SQL Database SQL Data Warehouse Data Factory Machine Learning Power BI

35. SQL Database
Managed relational database
platform
• Platform as a Service (PaaS)
SQL Server database online
Based on SQL Server 2016
New features introduced on
updates

36. SQL Database Specifications
• Basic, Standard, and Premium
tiers
• Update 1 TB storage per shard
• Elastic database features (shards)
• Up to 35 days automatic backup
• Up to 1750 DTUs (database
throughput units)

37. SQL Database Benefits
• Built-in high availability
• Automatic disaster recovery
• Performance governance
• Minimal maintenance
• Scale-out growth
• Azure first development

38. Create SQL Database
38

39. Azure
SQL Database Demo
39

40. SQL Data
Warehouse
Storage SQL Database SQL Data Warehouse Data Factory Machine Learning Power BI

41. Microsoft Azure SQL Data Warehouse
 MPP Architecture
 Dynamic Scaling
 SQL Server Experience
 Bring All Your Data

42. • Massively parallel processing
• Main control node
• Many compute nodes
• Distributed queries
• Data movement service
• Columnstore architecture
MPP Architecture

43. Grow, shrink, and pause
Many nodes based on scale
• Data Warehouse Throughput
Units (DWU)
Compute scales with DWU
Dynamic Scaling

44. • T-SQL Language
• Stored procedures
• User defined functions
• Indexes and partitioning
• Polybase integration
SQL Server Experience

45. • Relational database
• Structured data
• Unstructured data
• Polybase
Bring All Your Data

46. Create SQL Data Warehouse
46

47. Azure
SQL Data Warehouse Demo
47

48. 48
Which
database type
should we
use?

49. 49
You
picked
SQL DW!!

50. Building Tables
Compressed heaps by default
Selected distribution types
Define index type inline
Leverage typical DDL

51. Distribution Types
Round Robin
• Random, even distribution
• Ideal for most dimensions
• Ideal for uneven facts
Hash
• Distributed on a value
• Ideal for fact tables
• Distribution data dependent

52. Creating Tables
CREATE TABLE dbo.TableName (
Column1 int
,Column2 varchar(10)
)
WITH
(
DISTRIBUTION={distribution_type}
,CLUSTERED COLUMNSTORE INDEX
)

53. Polybase and SQL DW
Platform connectivity
• Hortonworks
• Cloudera
• HDInsight
• Azure storage
• SQL Database
Integrate many data types
• Relational
• Non-relational
Scales with SQL DW compute

54. Key Polybase T-SQL Commands
CREATE MASTER KEY
CREATE DATABASE SCOPED CREDENTIAL
CREATE EXTERNAL DATA SOURCE
CREATE EXTERNAL FILE FORMAT
CREATE EXTERNAL TABLE (AS… SELECT)

55. CTAS and CETAS
• Leverage SELECT to inherit schema
• Determine target schema at run-
time
• Indexing
• Partitioning
• Distribution

56. Integrate with Other Platforms
 More than just Polybase
 Connect using SQL connection
 Similar to using SQL Server
 Integrate with other tools

57. Azure
SQL Data Warehouse Demo
57

58. Data Factory
Storage SQL Database SQL Data Warehouse Data Factory Machine Learning Power BI

59. • Some initial issues noted
• Files use delimiters in data
• Data is longer than defined
• Times are impossible
Need to Clean Some Files

60. Azure Data Factory
• Compose storage, movement,
and processing pipelines
• Transform structured and
unstructured data
• Work with on-premises and
cloud data
• Monitor data pipeline health
• Visualize data lineage

61. Azure Data Factory
61
Not 100
level content

62. Machine
Learning
Storage SQL Database SQL Data Warehouse Data Factory Machine Learning Power BI

63. Machine Learning
Model predictions
Production Ready Models
Integrate via Web Service
Scale on demand
Leverage existing investments
• R
• Pyhton

64. Machine Learning

65. Predict the likelihood
that an aircraft incident
includes deer?
Do you remember those deer?
65

66. Azure
Machine Learning Demo
66

67. Power BI
Storage SQL Database SQL Data Warehouse Data Factory Machine Learning Power BI

68. Collection of tools
• Power Query
• Power Map
• Power View
• Power Pivot
Self-service BI/mash-up/visualizations
• Excel
• Power BI website
• Power BI desktop
Power BI
68

69. Business Intelligence Lifecycle
Module 1
Data
Extraction
Data
Modeling
Data
Presentation

70. Databases
Flat Files
Reporting
Services
Cloud
Hadoop
SharePoint Lists
Internet
Active Directory
Facebook
Relationships
Calculations
Key Performance
Indicators
Tables
Charts
Maps
Exporting
Tables
Charts
Apps For Office
3-D Maps
Hierarchies

71. Azure
Power BI Demo
71

72. • Data Lake Store
• Stream Analytics
• HDInsight
• DocumentDB
• Azure Search
• Event Hub
• IoT Hub
But wait… there’s more

73. 73
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74. 74
Session Evaluations
ways to access
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conference venue and in the
program guide
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Friday November 6th to
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75. Thank You