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DBI321. Building BI Solutions with SQL Server PDW AU3. Matt Peebles, Artin Avanes Microsoft Corporation. Agenda. Trends in the DW space How does SQL Server PDW fit in? SQL Server PDW AU3 – What’s new? Building BI Solutions with SQL Server PDW Customer Successes

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building bi solutions with sql server pdw au3

DBI321

Building BI Solutions with SQL Server PDW AU3

Matt Peebles, Artin Avanes

Microsoft Corporation

agenda
Agenda
  • Trends in the DW space
  • How does SQL Server PDW fit in?
  • SQL Server PDW AU3 – What’s new?
  • Building BI Solutions with SQL Server PDW
    • Customer Successes
    • Using SQL Server PDW with Microsoft BI solutions
    • Using SQL Server PDW with third party BI solutions
    • BI solutions leveraging Hadoop integration
  • What’s coming next in SQL Server PDW?
slide3

Trends in the Data Warehousing Space

Understanding the Opportunity

  • Performance at scale: ability to analyze massive amounts of data
  • DW systems continue to grow at a fast pace, scalabilityis a key concern, growing a system from 10s of TBs, to 100s of TB, to PBs

Data Warehousing has shifted almost entirely towards the appliance model due to speed of the balanced appliance and scalability of scale out (MPP) solutions.

Jim Cobelius, Forrester Research

Source: TDWI Report – Next Generation DW

slide4

Trends in the Data Warehousing Space

Understanding the Opportunity

  • Appliances are the key trend in the next 4 years (4 Billion market by ‘15)
  • Cloud DW longer-term
  • Box is a slow decline

CAGR

Share(‘15)

7.1%

4.6%

7.1%

5.0%

30.0%

26.2%

-0.3%

60.4%

Source: MS internal analysis, DBSMIT Cloud Market Opportunity Forecast

agenda1
Agenda
  • Trends in the DW space
  • How does SQL Server PDW fit in?
  • SQL Server PDW AU3 – What’s new?
  • Building BI Solutions with SQL Server PDW
    • Customer Successes
    • Using SQL Server PDW with Microsoft BI solutions
    • Using SQL Server PDW with third party BI solutions
    • BI solutions leveraging Hadoop integration
  • What’s coming next in SQL Server PDW?
slide6

What is Parallel Data Warehouse (PDW)?

SQL Server Data Warehousing in Appliance Model

Scale out

Scalable

Standards

Based

Flexible

Cost

Effective

pdw hardware architecture
PDW Hardware Architecture

Control Rack

Compute Racks (1/2 to 4)

Storage Nodes

Compute Nodes

Control Nodes

Active / Passive

Client Drivers

Management Nodes

Data Center Monitoring

Dual Fiber Channel

Dual Infiniband

Landing Zone

ETL Load Interface

Backup Node

Corporate Backup Solution

Spare Compute Node

Corporate Network

Appliance Network

pdw data example

Time Dim

Product Dim

Date Dim ID

Calendar Year

Calendar Qtr

Calendar Mo

Calendar Day

Prod Dim ID

Prod Category

Prod Sub Cat

Prod Desc

Store Dim

Store Dim ID

Store Name

Store Mgr

Store Size

PDW Data Example

PDW Compute Nodes

SQL

SQL

SQL

SQL

Sales Facts

Date Dim ID

Store Dim ID

Prod Dim ID

Mktg Camp Id

Qty Sold

Dollars Sold

Mktg

Campaign Dim

Mktg Camp ID

Camp Name

Camp Mgr

Camp Start

Camp End

pdw data example1

Time Dim

Product Dim

Date Dim ID

Calendar Year

Calendar Qtr

Calendar Mo

Calendar Day

Prod Dim ID

Prod Category

Prod Sub Cat

Prod Desc

Store Dim

Store Dim ID

Store Name

Store Mgr

Store Size

PDW Data Example

Smaller Dimension Tables are Replicated on Every Compute Node

SQL

SQL

SQL

SQL

PD

TD

MD

SD

PD

TD

MD

SD

Sales Facts

Date Dim ID

Store Dim ID

Prod Dim ID

Mktg Camp Id

Qty Sold

Dollars Sold

PD

TD

SD

MD

PD

TD

MD

SD

Mktg

Campaign Dim

Mktg Camp ID

Camp Name

Camp Mgr

Camp Start

Camp End

pdw data example2

Time Dim

Product Dim

Date Dim ID

Calendar Year

Calendar Qtr

Calendar Mo

Calendar Day

Prod Dim ID

Prod Category

Prod Sub Cat

Prod Desc

Store Dim

Store Dim ID

Store Name

Store Mgr

Store Size

PDW Data Example

Larger Fact Table is Hash Distributed Across All Compute Nodes

SQL

SQL

SQL

SQL

PD

SF-1

TD

MD

SD

SF-2

PD

TD

MD

SD

Sales Facts

SF-3

SF-4

SF-1

SF-2

Date Dim ID

Store Dim ID

Prod Dim ID

Mktg Camp Id

Qty Sold

Dollars Sold

SF-3

PD

TD

SD

MD

SF-4

PD

TD

MD

SD

Mktg

Campaign Dim

Mktg Camp ID

Camp Name

Camp Mgr

Camp Start

Camp End

sql server parallel data warehouse a quick look at mpp query execution
SQL Server Parallel Data WarehouseA quick look at MPP query execution

The actual user data resides on compute nodes, and stepsof the global execution plan are executed on each compute node

SQL Server PDW Appliance

Client

Control Node

Compute Node 1

SQL Server PDW is a shared nothing MPP system, meaning user data is distributed across the nodes*. Data Movement Serviceis responsible for moving data around so that individual nodes can satisfy queries that need data from other nodes.

Compute Node 2

The user connects to ‘the appliance’likehe would to a ‘normal’ SQL Server, and sends his request

The control node handles global query execution, and generates a distributed execution plan

.

.

.

Compute Node N

dealing with distributions shuffling
Dealing with Distributions - Shuffling

Example:

Select [color], SUM([qty]) from [Store Sales] group by [color];

Return

Distributed Table

Compute Node 2

Compute Node 1

Temp_1

Shuffle Movement

DMS Redistributes the data

by color values in parallel.

Store Sales

color

qty

Ss_id

color

qty

Hash

Red

5

Red

5

1

Red

8

Blue

11

3

Parallel Merge

and Aggregate

Red

12

Red

12

5

color

qty

Green

7

Green

7

7

Blue

21

Hash

Hash

Green

7

Red

25

Temp_1

Store Sales

Yellow

12

color

qty

Ss_id

color

qty

Blue

11

Red

8

2

Hash

Blue

10

Blue

10

4

Yellow

12

Yellow

12

6

slide13

SQL Server Parallel Data WarehouseOverall Architecture

Control Rack

Data Rack (up to 4)

Control Node

Compute Node 1

DMS Core

PDW Engine

Client Interface

(JDBC, ODBC,

OLE-DB, ADO.NET)

PDW Agent

DMS Manager

Compute Node 2

PDW Agent

DMS Core

PDW Agent

Landing Zone Node

ETL

Interface

Bulk Data Loader

PDW Agent

Management Node

Compute Node 10

Active Directory

DMS Core

Legend:

PDW Agent

PDW Agent

PDW service

PDW

=

Parallel Data Warehouse

DMS

=

Data Movement Service

agenda2
Agenda
  • Trends in the DW space
  • How does SQL Server PDW fit in?
  • SQL Server PDW AU3 – What’s new?
  • Building BI Solutions with SQL Server PDW
    • Customer Successes
    • Using SQL Server PDW with Microsoft BI solutions
    • Using SQL Server PDW with third party BI solutions
    • BI solutions leveraging Hadoop integration
  • What’s coming next in SQL Server PDW?
slide15

SQL Server Parallel Data Warehouse AU3

Release Themes

Performance

At Scale

BI, Analytics, & ETL Integration

SQL Server

Compatibility

Less work for the same results

Do the same work more efficiently

  • Native Support for
  • Analysis Services
  • Reporting Services
  • PowerPivot
  • Lay the foundation for broad connectivity support

Broader functionality

Full Alignment

slide16

SQL Server PDW Architecture

How did it work before?

  • Problem
    • Basic RDBMS functionality, that already exists in SQL Server, was re-built in PDW 
  • Challenge for PDW AU3 release
    • Can we leverage SQL Server and focus on MPP related challenges?

Control Node

slide17
SQL Server PDW AU3 Architecture PDW AU3 Architecture with Shell Appliance and Cost-Based Query Optimizer

SQL Server runs a ‘Shell Appliance’

Every database exists as an empty ‘shell’

  • All objects, no user data

DDL executes against both the shell and the compute nodes

Large parts of basic RDBMS functionality now provided by the shell

  • Authentication and authorization
  • Schema binding
  • Metadata catalog

SELECT

SELECT

Engine Service

Shell Appliance

(SQL Server)

foo

Control Node

Plan Steps

Plan Steps

Plan Steps

Compute Node

(SQL Server)

Compute Node

(SQL Server)

Compute Node

(SQL Server)

foo

foo

foo

slide18
SQL Server PDW AU3 Architecture PDW AU3 Architecture with Shell Appliance and Cost-Based Query Optimizer
  • User issues a query
  • Query is sent to the Shell through sp_showmemo_xml stored procedure
    • SQL Server performs parsing, binding, authorization
    • SQL optimizer generates execution alternatives
  • MEMO containing candidate plans, histograms, data types is generated
  • Parallel execution plan generated
  • Parallel plan executes on compute nodes
  • Result returned to the user

SELECT

SELECT

Engine Service

Shell Appliance

(SQL Server)

Control Node

MEMO

Return

Plan Steps

Plan Steps

Plan Steps

Compute Node

(SQL Server)

Compute Node

(SQL Server)

Compute Node

(SQL Server)

pdw cost based optimizer optimizer lifecycle
PDW Cost-Based OptimizerOptimizer lifecycle…

1. Simplification and space exploration

  • Query standardization and simplification (e.g. column reduction, predicates push-down)
  • Logical space exploration (e.g. join re-ordering, local/global aggregation)
  • Space expansion (e.g. bushy trees – dealing with intermediate resultsets)
  • Physical space exploration
  • Serializing MEMO into binary XML (logical plans)
  • De-serializing binary XML into PDW Memo

2. Parallel optimization and pruning

  • Injecting data move operations (expansion)
  • Costing different alternatives
  • Pruning and selecting lowest cost distributed plan

3. SQL Generation

  • Generating SQL Statements to be executed
pdw cost based optimizer and cost model details
PDW Cost-Based Optimizer… And Cost Model Details
  • PDW cost model assumptions:
    • Costing only data movement operations (relational operations excluded)
    • Sequential step execution (no pipelined and independent parallelism)
  • Data movement operations consist of multiple tasks
  • Each task has Fixed and Variable overhead
  • Uniform data distribution assumed (no data skew)
pdw sales test workload au2 to au3
PDW Sales Test WorkloadAU2 to AU3
  • 5x improvement in terms of total elapsed time out of the box

Seconds

Queries

theme performance at scale z ero data conversions in data movement
Theme: Performance at ScaleZero data conversions in data movement

Goal

  • Eliminate CPU utilization spent on data conversions
  • Further parallelize operations during data moves

Functionality

  • Using ODBC instead of ADO.NET for reading and writing data
  • Minimizing applianceresource utilizationfor data moves

Benefits

  • Betterresource, CPU, utilization
  • 6x or more faster moveoperations
  • Increased concurrency
  • Mixed workload (loads + queries)
theme sql server compatibility sql server security and metadata
Theme: SQL Server CompatibilitySQL Server Security and Metadata

Security

  • SQL Server security syntax and semantics
  • Supporting user, rolesandlogins
  • Fixed database roles
  • Allows script re-use
  • Allows well-known security methods

Metadata

  • PDW metadata stored in SQL Server
  • ExistingSQL Server metadata tables/views (e.g. security views)
  • PDW distribution info as extended propertiesin SQL Servermetadata
  • Existing means and technology for persisting metadata
  • Improved 3rdpartytool compatibility(BI, ETL)
theme sql server compatibility support for sql server native client
Theme: SQL Server CompatibilitySupport for SQL Server (Native) Client

Goal

  • ‘Look’ just like a normal SQL Server
  • Better integration with other BI tools

Functionality

  • Useexisting SQL Server drivers to connect to SQL Server PDW
  • ImplementSQL Server TDSprotocol
  • Named Parameter support
  • SQLCMD connectivityto PDW

Benefits

  • Use known tools and proven technology stack
  • ExistingSQL Server ’eco-system’
  • 2x performance improvementfor return operations
  • 5x reduction of connection time

Server: 10.217.165.13, 17001

TDS

SQL Server Clients

(ADO.NET, ODBC,

OLE-DB, JDBC)

SequeLink

SQL PDW Clients

(ODBC, OLE-DB, ADO.NET)

Server: 10.217.165.13, 17000

theme sql server compatibility stored procedure support subset
Theme: SQL Server CompatibilityStored Procedure Support (Subset)

Syntax

Goal

  • Support common scenarios of code encapsulation and reuse in Reporting and ETL

Functionality

  • System and user-defined stored procedures
  • Invocation using RPC or EXECUTE
  • Control flow logic, input parameters

Benefits

  • Enables common logic re-use
  • Big impact for Reporting Services scenarios
  • Allows portingexisting scripts
  • Increases compatibilitywith SQL Server

CREATE { PROC | PROCEDURE } [dbo.]procedure_name

    [ { @parameter  data_type } [ = default ] ] [ ,...n ]

AS { [ BEGIN ] sql_statement [;] [ ...n ] [ END ] } [;]

ALTER { PROC | PROCEDURE } [dbo.]procedure_name

[ { @parameter data_type } [ = default ]    ] [ ,...n ]

AS { [ BEGIN ] sql_statement [;] [ ...n ] [ END ] } [;]

DROP { PROC | PROCEDURE } { [dbo.]procedure_name } [;]

[ { EXEC | EXECUTE } ]

  {

    { [database_name.][schema_name.]procedure_name }

      [{ value | @variable }] [ ,...n ]

  } [;]

{ EXEC | EXECUTE }

  ( { @string_variable | [ N ]'tsql_string' } [ + ...n ] ) [;]

Unsupported Functionality

Stored Proc Nesting

Output Params

Return

Try-Catch

theme sql server compatibility collations
Theme: SQL Server CompatibilityCollations

Syntax

Goal

  • Support local and international data

Functionality

  • Fixed server level collation
  • User-defined column level collation
  • Supporting all Windows collations
  • Allow COLLATE clauses in Queries and DML

Benefits

  • Storeall the data in PDW w/ additional querying flexibility
  • ExistingT-SQL DDLand Query scripts
  • SQL Server alignmentand functionality

CREATE TABLE T (

c1 varchar(3) COLLATEtraditional_Spanish_ci_ai,

c2 varchar(10) COLLATE …)

SELECT c1 COLLATE Latin1_General_Bin2

FROM T

SELECT * FROM T

ORDER BY c1 COLLATE Latin1_General_Bin2

  • Unsupported Functionality
  • Cannot specify DB collation during DB creation
  • Cannot alter column collations for existing tables
theme improved integration sql server pdw connectors
Theme: Improved IntegrationSQL Server PDW Connectors

Connector for Hadoop

  • Bi-directional(import/export) interfacebetween MSFT Hadoop and PDW
  • Delimited file support
  • Adapter uses existing PDW tools (bulk loader, dwsql)
  • Low cost solution that handles all the data: structured and unstructured
  • Additional agility, flexibilityand choice

Connector for Informatica

  • Connector providing PDW source and target (mappings, transformations)
  • InformaticausesPDW bulk loader for fast loads
  • Leverage existing toolset and knowledge

Connector for Business Objects

agenda3
Agenda
  • Trends in the DW space
  • How does SQL Server PDW fit in?
  • SQL Server PDW AU3 – What’s new?
  • Building BI Solutions with SQL Server PDW
    • Customer Successes
    • Using SQL Server PDW with Microsoft BI solutions
    • Using SQL Server PDW with third party BI solutions
    • BI solutions leveraging Hadoop integration
  • What’s coming next in SQL Server PDW?
pdw retail pos workload original customer smp solution vs pdw au3 with cost based query optimizer
PDW Retail POS WorkloadOriginal Customer SMP solution vs. PDW AU3 (with cost-based query optimizer)

Seconds

Queries

customer successes how are customers using pdw bi
Customer SuccessesHow are customers using PDW & BI ?

CUSTOMER EXAMPLE:

Stock Exchange in the US

Data Volume

  • 80 TB data warehouse analyzing data from exchanges
  • Existing system based on SQL SMP farm
    • 2 different clusters of 6 serverseach

Requirement

  • Linear scalability with additional hardware
  • Support hourly loads with SSIS – 300GB/day
  • BI Integration: SSRS, SSAS and PowerPivot

AU3 Feedback

  • SP and increased T-SQL support was great
  • Migrating SMP SSRS to PDW was painless
  • 142x for scan heavy queries & no summary tables
  • Enabled queries that do not run on existing system

Reports

Portal

Dashboards

ETL

Scorecards

PDW

Operational DB’s

customer successes cont d how are customers using pdw bi
Customer Successes – cont’dHow are customers using PDW & BI ?

CUSTOMER EXAMPLE:

Major Retailer in the US

Data Volume

  • 36 TB data warehouse analyzing data from transactional and clickstream sources
  • Business need to expand to 7 year data window (currently 1 year data)

Requirements

  • Scalability - growing data volume does not affect performance
  • Performance and ad-hoc analysis for interactive querying by users
  • BI Integration with Microsoft BI stack - SSAS and SSRS

AU3 Feedback

  • SSAS cubes worked ‘out-of-box’
  • Performance an order of magnitude faster than existing system (~30x on an expanded data set)
agenda4
Agenda
  • Trends in the DW space
  • How does SQL Server PDW fit in?
  • SQL Server PDW AU3 – What’s new?
  • Building BI Solutions with SQL Server PDW
    • Customer Successes
    • Using SQL Server PDW with Microsoft BI solutions
    • Using SQL Server PDW with third party BI solutions
    • BI solutions leveraging Hadoop integration
  • What’s coming next in SQL Server PDW?
role of pdw within the bi stack
Role of PDW within the BI stack

PDW role as fast ‘data hub’

  • Fast and parallel feeding of data marts (DMs) via Infiniband
    • CREATE REMOTE TABLE AS SELECT
  • Aggregation abilities avoids ETL overhead in existing systems
    • No need for indexes
    • No need to maintain indexed/materialized views (summary tables)

GBit link

SSAS / SSRS

DM

DM

SSAS / SSRS

Infiniband

PDW

SSAS / SSRS

DM

3rd party BI

ssas with sql server pdw understanding the differences compared to smp world
SSAS with SQL Server PDWUnderstanding the differences compared to ‘SMP world’

Specific to PDW

  • PDW does not support foreign key constraints
  • Shared nothing model requires careful data design and retrieval planning
  • Design cubes for parallel processing – via MOLAP & ROLAP storage model

Specific to the nature of large data

  • Parallel cube processing/deployment has its limits
    • Cautious about parallel loads of SSAS - query timeout settings
  • Query design crucial - only include required data
    • BI tools traditionally not designed for handling huge amount of data
agenda5
Agenda
  • Trends in the DW space
  • How does SQL Server PDW fit in?
  • SQL Server PDW AU3 – What’s new?
  • Building BI Solutions with SQL Server PDW
    • Customer Successes
    • Using SQL Server PDW with Microsoft BI solutions
    • Using SQL Server PDW with third party BI solutions
    • BI solutions leveraging Hadoop integration
  • What’s coming next in SQL Server PDW?
supported third party bi solutions
Supported Third Party BI Solutions
  • AU3 T-SQL compatibility allows for common access for multiple tools
  • Current support on PDW drivers includes
    • Microstrategy
    • BusinessObjects
    • Cognos
  • Other tools have ‘mixed experience’
    • Cognossupport required : CURRENT_TIMESTAMP , @@DATEFIRST, SET OPTION …
    • Core connectivity enhancements planned for the next 2 releases
agenda6
Agenda
  • Trends in the DW space
  • How does SQL Server PDW fit in?
  • SQL Server PDW AU3 – What’s new?
  • Building BI Solutions with SQL Server PDW
    • Customer Successes
    • Using SQL Server PDW with Microsoft BI solutions
    • Using SQL Server PDW with third party BI solutions
    • BI solutions leveraging Hadoop integration
  • What’s coming next in SQL Server PDW?
new challenges for business analytics
New Challenges for Business Analytics
  • Huge amount of data born ‘unstructured’
  • Increasing demand for (near) real-time business analytics
  • Pre-filtering of important from less relevant raw data required

Applications

  • Sensor networks & RFID
  • Social networks & Mobile Apps
  • Biological & Genomics

HADOOP

Sensor/RFID Data

Web Data

Blogs, Docs

hadoop as a platform solution in the context of etl bi and dw
Hadoop as a Platform SolutionIn the context of ETL , BI , and DW
  • Platform to accelerate ETL processes (not competing with current ETL software tools!)
  • Flexible and fast development of ‘hand-written’ refining requests of raw data
  • Active & cost effective data archive to let (historical) data ‘live forever’
  • Co-existence with a relational DW (not completely replacing it !)
importing hdfs data into pdw for advanced bi
Importing HDFS data into PDW for advanced BI

Application Programmers

DBMS Admin

Power BI Users

SQOOP

HADOOP

SQL Server PDW

Sensor/RFID Data

Web Data

Blogs, Docs

Interactive BI/Data Visualization

hadoop pwd integration via sqoop export
Hadoop - PWD Integration via SQOOP (export)

SQOOP export with source (HDFS path) & target (PDW DB & table)

Copies incoming data on Landing Zone

  • PDW HadoopConnector

Read HDFS data via mappers

Compute Node 1

Compute Node 8

Invokes‘DWLoader’

  • FTP Server
  • Telnet Server
  • 1.
  • 3.
  • 2.
  • 4.
  • 5.

HDFS

Landing Zone

  • PDW-configuration file

Compute Nodes

Control Node

Linux/Hadoop

Windows/PDW

agenda7
Agenda
  • Trends in the DW space
  • How does SQL Server PDW fit in?
  • SQL Server PDW AU3 – What’s new?
  • Building BI Solutions with SQL Server PDW
    • Customer Successes
    • Using SQL Server PDW with Microsoft BI solutions
    • Using SQL Server PDW with third party BI solutions
    • BI solutions leveraging Hadoop integration
  • What’s coming next in SQL Server PDW?
sql server pdw roadmap w hat is coming next
SQL Server PDW Roadmap What is coming next?

CALENDAR YEAR 2011

CALENDAR YEAR 2012

Q3

Q1

Q2

Q3

Q4

Q2

Q4

Q1

Shipped

Shipped

Shipped

Appliance Update 1

Appliance Update 2

V-Next

Appliance Update 3

  • Improved node manageability
  • Better performance and reduced overhead
  • OEM requests
  • Cost based optimizer
  • Native SQL Server drivers, including JDBC
  • Collations
  • More expressive query language
  • Data Movement Services performance
  • SCOM pack
  • Stored procedures (subset)
  • Half-rack
  • Columnar store index
  • Stored procedures
  • Integrated Authentication
  • PowerView integration
  • Workload management
  • LZ/BU redundancy
  • Windows 8
  • SQL Server 2012
  • Hardware refresh
  • Programmability
    • Batches
    • Control flow
    • Variables
  • Temp tables
  • QDR infiniband switch
  • Onboard Dell
  • 3rd party integration (Informatica, MicroStrategy, Business Objects, HADOOP)
in review
In Review
  • Session Objectives
    • Provide an overview of SQL Server PDW
    • Introduce PDW AU3 and share details regarding the new features and their impact on BI scenarios
  • Key Takeaways
    • PDW is the SQL Server DW Appliance for 10-100s TB
    • AU3 enables you to use your existing BI solutions on Microsoft & 3rd Party BI Tools
    • Expect at least 5x performanceimprovements over PDW AU2
      • Specific workloads can see much more
related content
Related Content
  • DBI209 – Big Data, Big Deal

Lots of BI Tool Specific Related Sessions (PowerPivot, Analysis services, Etc.)

Breakthrough Insights: Big Data Analytics & Data Warehousing Demo Station

PDW Deep Dive Session Online from TechEd 2010

track resources
Track Resources

Hands-On Labs

@sqlserver

@ms_teched

SQL Server 2012 Eval Copy

Get Certified!

mva

Microsoft Virtual Academy

resources
Resources

Learning

TechNet

  • Connect. Share. Discuss.
  • Microsoft Certification & Training Resources

http://northamerica.msteched.com

www.microsoft.com/learning

  • Resources for IT Professionals
  • Resources for Developers
  • http://microsoft.com/technet

http://microsoft.com/msdn

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slide52

© 2012 Microsoft Corporation. All rights reserved. Microsoft, Windows, Windows Vista and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries.

The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.