J1 - Keynote Data Platform - Rohan Kumar MS Cloud Summit 2017

1. Bienvenue.

2. Une conférence communautaire

3. Connect, Share, Learn
This is Community

4. They are Community

5. Merci à nos partenaires
Presse Organisateurs

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8. Rohan Kumar
General Manager
Database Systems
Microsoft Corp., Redmond
Data Platform Keynote

12. IntelligenceCloudBig Data & IoT
Three major trends are converging

13. How successful companies are staying ahead
Exploring new
business opportunities
with data-driven
services
Getting the right
products to the right
places with inventory
management
Offering customers
exactly what they want,
when they want it, with
personalization
Fixing problems
proactively before they
start with predictive
maintenance

14. Database
+ Big Data
Information
Management
Machine Learning
+ Analytics
Intelligence Dashboards +
Visualizations

15. Database
+ Big Data
Information
Management
Machine Learning
+ Analytics
Intelligence Dashboards +
Visualizations
1010
0101
0010
{}
Across any data any platform any language
T-SQL
Java
PHP
Node.js
C/C++
C#/VB.NET
Python
Ruby

16. Customer priorities
Optimize IT Business Transformation

17. Microsoft solutions
Optimize IT Business Transformation
Intelligent
platform for
SaaS apps
Self-managed
services for
reduced OPEX
Modern data
platform for
high ROI
Integrated intelligence
for breakthrough
experiences

18. SaaS
Why cloud, why now?
Organizations adopting business SaaS
apps to reduce CAPEX + OPEX
For software providers, big opportunity
for growth—30% of enterprise app
revenue by 2018
Ship innovations to customers faster
Preliminary IDC Hosted Dedicated Private Cloud Services Forecast (4Q2014)
Enterprise apps revenue share
2013 2014 2015 2016 2017 2018
SaaS
On-premise
$50B
SaaS
revenue
worldwide

19. Why Azure for building high-growth SaaS apps
Drive operational
efficiency
Scale costs with
performance and
optimize your apps
Protect your
customer’s data
Secure your data
and apps with
built-in tools
Create engaging
experiences
Engage users with
rich visualizations
and analytics
Fuel growth
Scale apps globally on
hybrid platforms or in
the cloud

20. Azure DocumentDB
Blazing fast, planet-scale NoSQL
Lower TCO
Less expensive than
running NoSQL
databases
Infinite, global scale
Scale from 100 to 10s
of millions of
requests/sec
Guaranteed
performance
Guaranteed low latency
for reads and writes
Build and ship code
faster
Support for SQL, Java,
MongoDB

21. Azure SQL Database
Intelligent, scalable database service
Lower TCO
53% less expensive
than on-prem/hosted
Faster time
to market
75% faster app
deployment cycles
Manage thousands
of DBs as one
47% staff hours
reclaimed for other
tasks
Customer
1
Customer
…500
Customer
2
Greater security
Built-in security with AI-
based Threat Detection
SECURITY

22. Saved $¼ Million
Sped dev cycle 2x

24. App Migration
Why thousands?
Long-time challenge for IT
Manage long tail of tactical apps at scale
Reduce burden on uptime and security
406% 98%
53%Less expensive than
on-prem/hosted
ROI Less DB-related
downtime
47%Increase in staff
efficiencies
Source: IDC White Paper | The Business Value of Microsoft Azure SQL Database Services

25. Migrating databases to Azure
Azure SQL Database
SQL Server in a VM
Migration Tools

26. The MS IT Example
40,000 databases, across
15,000 SQL Server instances
GOAL: Reduce costs and
demands on IT
1 DB Assessment
53%SQL Database
potentially ready
to be migrated
Migration2

27. Modernize
critical applications
Security and data protection a top concern
Increasing performance requirements as
demands grow
Pressure to deliver the best service and
most engaging experiences
Ingest real-time
train data:
Brakes are hot!
Query across
historical data:
They’ve been hot
for 4 hours!
Analyze global trends:
Could lead to accident

28. TPC-H
Oracle
is #5#2
SQL Server
#1
SQL Server
#3
SQL Server
at massive scale
1M
Predictions
per second
The power of SQL Server: Everything built-in
Any platform Any data
1010
0101
0010
{}
Any language
T-SQL
Java
PHP
Node.js
C/C++
C#/VB.NET
Python
Ruby
with in-memory OLTP
Most secure
database
Self-service BI per user
National Institute of Standards and Technology Comprehensive Vulnerability Database update 5/4/2015

29. In-database Analytics (R)
In-memory OLTP & DW
Operational Analytics
Compression & Partitioning
PolyBase
Always Encrypted
Row-level Security & Data Masking
Enterprise Standard Express

30. In-database Analytics (R)
In-memory OLTP & DW
Operational Analytics
Compression & Partitioning
PolyBase
Always Encrypted
Row-level Security & Data Masking
Enterprise Standard Express

31. HTAP built in to
SQL Server 2016
Up to 100x faster analytical queries
Queries from minutes to seconds
Up to 30x faster transactions with
in-memory OLTP
Transforms business process
01001010101
In-memory
ColumnStore
In-memory
OLTP
Real-time
business problem
detection

32. Industry-leading
data warehousing
performance
Oracle
is #5#2
SQL
Server
#1
SQL
Server
#3
SQL
Server
Up to 100x faster analytical queries
ETL services built-in
PolyBase for single T-SQL query
across relational and Hadoop

33. R built-in for 1M
predictions/sec
Predicting loan defaults
Store
Predictions
In-memory
OLTP
ColumnStore Power BI
dashboard
In-Database
analytics
at scale
R
Prepare
for analytics
Visualize
Data from 8M
vehicle loans Predicts loan
defaults
Age, original balance, interest
rate, loan remaining months,
credit score
R enables users to leverage existing
tools with data where it already lives
Industry-leading innovation in artificial
intelligence to discover insights faster
Machine learning with 1,000,000+
predictions per second with real-
time R scoring

34. 100X Faster
with R
in SQL Server 2016

35. SQL Server R Services

36. Super-charge performance with
database engine enhancements
What’s coming in SQL Server vNext

37. Database engine enhancements
SQL Server on the platform of your choice
Linux Linux/Windows container
Windows
Windows Server
• Linux distributions including
RedHat Enterprise Linux (RHEL),
Ubuntu, and SUSE Enterprise Linux
(SLES)
• Docker: Windows & Linux
containers (and MacOS)
• Windows Server / Windows 10
• Package-based installation, yum
install, apt-get, and more options

38. Database engine enhancements
Mission critical HA/DR on Windows and Linux
• Availability Groups and Failover
Clustering now also work with
third party clustering technologies
like Pacemaker
• Availability Groups can now span
Windows and Linux or be Linux-
only
AlwaysOn
• Enables Testing
• Enables Migrations
• High Availability
• Offload Backups
• Scale BI Reporting
• Third Party
Clustering
Technology
Support

39. In-Memory OLTP Enhancements
New T-SQL enhancements for In-
Memory OLTP Tables and Natively
Compiled Stored Procedures
• JSON Support
• CROSS Apply
• Computed Columns Support
• Removed index limit
• CASE support
• Sp_rename/sp_spaceused support
• TOP (N) WITH TIES
• Improved Performance on ALTER
TABLE, failover operations
• Azure VM Support for In-Memory
Checkpoint Files
In-Memory
Tables
JSON
Computed Columns
CROSS APPLY
TOP
CASE
More Indexes

40. Columnstore Enhancements
Clustered Columnstore LOB Support
• LOBs are compressed, reducing DB size
• Queries run over the compressed
format, improving performance
• Reduced backup times
Online Non-Clustered Columnstore
Index Build/Rebuild
• Create and Rebuild Indexes without long
blocking
• Improved Support and Performance for
HTAP scenarios

41. Database engine enhancements
Adaptive query processing
• Interleaved
Compilation/Execution for
challenging queries to improve
plan quality and performance
• Adjusts memory grants for
repeated queries to avoid over
or under allocating
• Adaptive Joins adjust data
joining strategy dynamically
to improve query performance
and stability over skewed data
distributions
Improved efficiency with Adaptive Query Processing
Query
Memory
grant
Learn
Run query
Before
1 0 1 0 1 0
1 0 1 0 1 0
1 0 1 0 0 1
1 0
1 0 1 0 1 0
1 0 1 0
1 0 1 0 1 0
1 0 1 0 1 0
1 0 1 0 0 1
0 1 0 0
1 0 1 0 1 0
1 0 1 0 1 0
1 0 1 0 0 1
0 1 0 1 0 1
0 1 0
After
1 0 1 0 1 0
1 0 1 0 1 0
1 0 1 0 0 1
0 1 0 1 0 1
0 1 0 1 0 1
0 0 1 0 1 0
1 0 1 0 1 0
1 0 1 0 1 0
1 0 1 0 0 1
1 0 1 0 1 0
1 0 1 0 1 0
1 0 1 0 0 1
1 0 1 0 1 0
1 0 1 0 1 0
1 0 1 0 0 1
1 0 1
0 1 0
1 0 1
1 0 1
0 1 0
1 0 1
1 0 1
0 1 0
1 0 1
1 0 1
0 1 0
1 0 1
1 0 1 0 1 0
1 0 1 0 1 0
1 0 1 0 0 1
Adaptive
Query Processing
Greater
throughput

42. T-SQL Enhancements
• STRING_AGG string
concatenation aggregate
• CONCAT_WS, TRANSLATE,
TRIM string functions
• New Japanese Collation
Families
• New BULK Insert options and
CSV Support options
(including Azure Storage and
RFC 4180 CSV file support)

43. Database engine enhancements
Support for graph data
• Full CRUD support to create
nodes and edges
• Query language extension
provides multi-hop navigation
using join-free pattern matching
• SQL engine integration
enables querying across SQL
tables and graph data
• Existing tools work out of the
box with graph dataAdventure
Works
Statistics
Program
manager
Andy Smith
Business
analyst
Mary Jones
Bachelor
of Science,
Finance
Degree
earned
Position
Position
Employer
Employer
Role in
company
Role in
company
Skill
Skill
Coworker
Contoso
Former
employer
Role in
company
Professional networking app

44. • State-of-the-art Machine Learning algorithms v1
• Fast Tree, Fast Forest, Fast Linear, One Class SVM, Neural Nets with GPU
• Ease-of-Use
• Package installation / uninstallation
• Easy Model load and unload
• Automatic generation of T-SQL
• More data sources
• OLAP to R Connector

45. Transform
with Big Data + AI
Infinite scale to embrace decades of data
and real-time data as it’s created
Machine learning for predictive analytics to
look ahead at what may happen next
Cognition built-in for human-like
intelligence at scale across PBs of data
Intelligence
Cortana
Cognitive
Services
Bot
Framework
Preconfigured Solutions
Dashboards and Visualizations
Machine Learning and Analytics
Big Data Store
Information Management

46. Azure SQL Data Warehouse
True cloud elasticity for data warehousing
Azure
SQL Data Warehouse
Machine
Learning
Data Stores
BI Tools

47. Integrated cloud analytics solution
Rich visualizationsPetabyte-scale Speed-of-thought interactivity
Azure Analysis Services Power BIAzure SQL Data Warehouse

48. Switched off AWS to
Azure for higher
performance and
cost-savings

49. 10,000,000,000,000 rows
Analytics @ Petabyte Scale
using Azure SQL Datawarehouse

50. Petabyte Scale Azure SQL DW

51. Azure Data Lake Services
HDInsight
YARN
Managed clusters
Data Lake Store
HDFS
No-limits Data Lake
Data Lake Analytics
YARN
Analytics job service

52. Information
Management
Event Hubs
Data Catalog
Data Factory
Big Data Stores
SQL Data
Warehouse
Data Lake Store
Machine Learning
and Analytics
HDInsight
Stream Analytics
Data Lake
Analytics
Machine
Learning
Intelligence
Dashboards &
Visualizations
Cortana
Bot
Framework
Cognitive
Services
Power BI
Data
Sources
Apps
Sensors
and
devices
Action
People
Automated
Systems
Apps
Web
Mobile
Bots
Data Intelligence
Cortana Intelligence Suite
Transform data into intelligent action

53. Language
Speech
Search
Machine
Learning
Knowledge Vision
Spell
check
Speech API
Entity linking
Recommendation
API
Bing
autosuggest
Computer
vision
Emotion
Forecasting
Text to
speech
Thumbnail
generation
Anomaly
detection
Custom
recognition
(CRIS)
Bing
image search
Web language
model
Customer
feedback
analysis
Academic
knowledge
OCR, tagging,
captioning
Sentiment
scoring
Bing
news search
Bing
web search
Text analytics
Cognition

54. “Thousands of partners sign in to our platform every hour.
The response time from the Face API is incredible, enabling
us to verify our drivers without slowing them down.”
Dima Kovalev, Product Manager, Uber

55. Meeting customers where they are
Optimize IT Business Transformation
Intelligent
platform for
SaaS apps
Self-managed
services for
reduced OPEX
Modern data
platform for
high ROI
Integrated intelligence
for breakthrough
experiences

56. Database
+ Big Data
Information
Management
Machine Learning
+ Analytics
Intelligence Dashboards +
Visualizations