Microsoft Ignite /16/2017 5:47 PM

Microsoft Ignite 2015 4/16/2017 5:47 PM
© 2015 Microsoft Corporation. All rights reserved. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

Microsoft Analytics Platform System
Overview Matt Usher Senior Program Manager

Data Insights Conversation
4/16/2017 VISUALIZE + DECIDE Mobile Reports Natural language query Dashboards Applications Streaming CAPTURE + MANAGE Relational Internal & external  Non-relational NoSQL { } TRANSFORM + ANALYZE Orchestration Machine learning Modeling Information management Complex event processing Data TRANSFORM + ANALYZE VISUALIZE + DECIDE CAPTURE + MANAGE The Microsoft data platform © 2013 Microsoft Corporation. All rights reserved. Microsoft, Windows, 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.

System Center Marketing
4/16/2017 Cloud first Speed Agility Proven Feedback © 2012 Microsoft Corporation. All rights reserved. Microsoft, Windows, 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.

The traditional data warehouse
Microsoft Analytics Platform System 4/16/2017 The traditional data warehouse BI and analytics Dashboards Reporting Real-time data 2 Data warehouse ETL Increasing data volumes 1 New data sources and types 3 Cloud-born data 4 Data sources OLTP ERP CRM LOB Non-relational data Devices Web Sensors Social © 2014 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries.

Relational Data Warehouse
4/16/2017 Microsoft’s modern data warehouse BI & ANALYTICS Self-service Collaboration Corporate Predictive Mobile DATA ENRICHMENT AND FEDERATED QUERY SQL Server 2016 Extract, transform, load Single query model Data quality Master data management Analytics Platform System Azure SQL Data Warehouse DATA MANAGEMENT AND PROCESSING Azure HDInsight Box Software Relational Data Warehouse Box Software Hadoop Data Platform Appliances Cloud Appliances Cloud OLTP ERP CRM LOB Data sources Non-Relational Data Devices Web Sensors Social © 2012 Microsoft Corporation. All rights reserved. Microsoft, Windows, 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.

4/16/2017 Roadblocks to evolving to a modern data warehouse Keep legacy investment Acquire Big Data solution Buy new tier-one hardware appliance Acquire business intelligence Limited scalability and ability to handle new data types Significant training and data silos High acquisition and migration costs Complex with low adoption © 2014 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries.

Analytics Platform System Microsoft’s Big Data Appliance
Script is for Microsoft or partner speaker prep only – not for public distribution Analytics Platform System Microsoft’s Big Data Appliance MPP SQL Server Hadoop PolyBase Prebuilt & performance-tuned appliance Linear scale-out to petabytes of data MPP design & in-memory columnstore for significant speed improvement Dedicated region for Hadoop Joining relational & non-relational data with PolyBase © 2014 Microsoft Corporation. All rights reserved. Microsoft, Windows, 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.

4/16/2017 Microsoft Analytics Platform System The turnkey modern data warehouse appliance Enterprise-ready Big Data Next-generation performance at scale Engineered for optimal value © 2014 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries.

4/16/2017 APS delivers enterprise-ready Hadoop with HDInsight Manageable, secured, and highly available Hadoop integrated into the appliance SQL Server Parallel Data Warehouse Hadoop PolyBase High performance and tuned within the appliance End-user authentication with Active Directory 100-percent Apache Hadoop Managed and monitored using System Center Accessible insights for everyone with Microsoft BI tools © 2014 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries.

4/16/2017 Hadoop alone is not the answer to all Big Data challenges Steep learning curve, slow and inefficient Hadoop ecosystem Move HDFS into the warehouse before analysis New data sources Devices Web Sensor Social Learn new skills T-SQL New data sources Devices Web Sensor Social HDFS (Hadoop) Build Integrate Manage Maintain Support ETL Warehouse HDFS (Hadoop) “New” data sources © 2014 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries.

4/16/2017 Big Data insights for anyone New insights with familiar tools through native Microsoft BI integration Takes advantage of high adoption of Excel, Power View, PowerPivot, and SQL Server Analysis Services Minimizes IT intervention for discovering data with tools such as Microsoft Excel Everyone else using Microsoft BI tools Offers Hadoop tools like MapReduce, Hive, and Pig for data scientists Enables DBA and power users to join relational and Hadoop data with T-SQL Power users Data scientist © 2014 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries.

4/16/2017 Connecting islands of data with PolyBase Bringing Hadoop point solutions and the data warehouse together for users and IT Select… Result set Provides a single T-SQL query model for PDW and Hadoop with rich features of T-SQL, including joins without ETL Uses the power of MPP to enhance query execution performance Supports Windows Azure HDInsight to enable new hybrid cloud scenarios Provides the ability to query non-Microsoft Hadoop distributions, such as Hortonworks and Cloudera SQL Server Parallel Data Warehouse Microsoft Azure HDInsight PolyBase Hortonworks for Windows and Linux Cloudera Hadoop © 2014 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries.

4/16/2017 Unifying all of your data assets, cloud and on-premises Data Management Gateway for APS Office 365 Azure New for AU3: Connecting APS data with Power BI for Office 365 users Power BI site reports Azure DB Azure Machine Learning OData Feeds Tier 1 enterprise data hub Query on-premises data via Power BI Advanced analytics with Power BI combined with APS PolyBase Improved resiliency, high availability, and management Azure HDinsight Azure Stream Analytics Data Management Gateway service APS Other On Premise Data Sources Data Management Gateway OData Feeds PDW Hadoop SQL Server Oracle HDinsight Intranet © 2014 Microsoft Corporation. All rights reserved. Microsoft, Windows, 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.

Customer Scenario Build a Modern Data Warehouse
4/16/2017 Customer Scenario Young, High Growth Company Consumer facing devices Near real-time data Relational & Non-Relational Build a Modern Data Warehouse Cloud-born data Expected 15x Growth in 5 Years How to handle this growth? © 2014 Microsoft Corporation. All rights reserved. Microsoft, Windows, 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.

Customer was headed down 2 paths
4/16/2017 Customer was headed down 2 paths Analysis Services Enterprise BI Relational DWs Hadoop Azure Scale-out Azure IaaS Azure IaaS Azure HDInsight SharePoint Scale Up EDW Analysis Services Hadoop Enterprise BI SQL Server EE Azure IaaS Azure HDInsight SharePoint On-Premises Scale Up © 2014 Microsoft Corporation. All rights reserved. Microsoft, Windows, 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.

Our Approach Azure SQL Scale-up Financial & Functional Requirements
4/16/2017 Our Approach Determine Success Criteria 1 Worked with Local Microsoft Team to Determine Pricing 2 Introduced 3rd Option 3 What does the customer value? Minimize Cost Control over: Performance Reliability Scalability Min Admin Effort Based on expected growth – we ran the numbers... Analytics Platform System Azure SQL Scale-up Best Option based on Financial & Functional Requirements APS Business problem Financial Modeling Collaboration Business value © 2014 Microsoft Corporation. All rights reserved. Microsoft, Windows, 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.

Customer Architecture
4/16/2017 Customer Architecture Source systems ETL Delivery channels Master data MDM application Power BI Power Pivot data discovery MDM Hub Analysis server Cube ETL Device files Staging server ETL Parallel data warehouse Transaction data Staging Data warehouse SharePoint Extranet Phase 2 Power view reports and dashboards SSRS standard reports Excel services ETL Azure blob storage Windows Azure ML + HDInsight Big data POC Phase 3 Denote future phases © 2014 Microsoft Corporation. All rights reserved. Microsoft, Windows, 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.

In Summary The Modern Data Warehouse Three viable options considered
4/16/2017 In Summary Three viable options considered Worked with Customer to determine success criteria Worked with customer’s strategic SI to steward process The Modern Data Warehouse Weighed Financial & Functional Requirements © 2014 Microsoft Corporation. All rights reserved. Microsoft, Windows, 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.

Performance limitations and scale with a traditional data warehouse
Microsoft Analytics Platform System 4/16/2017 Performance limitations and scale with a traditional data warehouse Scale up Rowstore Data Querying data by row C1 C2 C3 C4 R1 R2 R3 R4 R5 R6 Page 1 Page 2 Page 3 Forklift Forklift Diminishing scale as requirements grow Sub-optimal performance for many data warehouse queries © 2014 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries.

4/16/2017 Scaling out your data to petabytes Scale-out technologies in the Analytics Platform System Scale out Multiple nodes with dedicated CPU, memory, and storage Ability to incrementally add hardware for near-linear scale to multiple petabytes Ability to handle query complexity and concurrency at scale No “forklift” of prior warehouse to increase capacity Ability to scale out HDInsight and PDW PDW / HDInsight PDW / HDInsight PDW / HDInsight PDW / HDInsight PDW / HDInsight PDW / HDInsight PDW 0 terabytes 6 petabytes 22 © 2014 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries.

4/16/2017 Blazing-fast performance MPP and In-Memory Columnstore for next-generation performance 23 Up to 100x faster queries Updateable clustered columnstore vs. table with customary indexing Up to 15x more compression Columnstore index representation C1 C2 C3 C4 C5 C6 Parallel query execution Store data in columnar format for massive compression Load data into or out of memory for next- generation performance with up to 60% improvement in data loading speed Updateable and clustered for real-time trickle loading Query Results © 2014 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries.

Moving from SQL Server to APS
4/16/2017 Moving from SQL Server to APS APS Why? Distributes data and query processing across multiple servers – eliminates bottlenecks inherent in SMP architecture Integrated storage is more cost effective over most SAN systems – lowest DW Appliance $$/TB in the industry Linear scale out to 6 petabytes of usable storage for DW Significantly less performance tuning over an SMP solution Seamless RDBMS and Hadoop integration with PolyBase Compute Node Management Control © 2014 Microsoft Corporation. All rights reserved. Microsoft, Windows, 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.

4/16/2017 Lowest price per TB for data warehouse appliance with APS High performance using commodity hardware Price per terabyte for leading vendors Significantly lower price per terabyte than the closest competitor Price per terabyte for user-available storage (compressed) $30 $25 $20 $15 Thousands $10 Lower storage costs with Windows Server 20124 Storage Spaces $5 $0 Oracle EMC IBM Teradata Microsoft NOTE: Orange line indicates average price per terabyte. 26 © 2014 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries.

4/16/2017 Value through a single flexible appliance solution Why Analytics Platform System when I have SQL Server? Simplify management with System Center Management Pack Reduce the data center footprint Reduce energy costs and usage Reduce tuning efforts while retaining high performance Accelerate time to value and insights without a forklift for scaling out SQL Server PDW Hadoop PolyBase © 2014 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries.

4/16/2017 Hardware and software engineered together The ease of an appliance Pre-configured, built, and tuned software and hardware Integrated support plan with a single Microsoft contact Co-engineered with HP, Dell, and Quanta best practices Leading performance with commodity hardware SQL PDW Hadoop PolyBase © 2014 Microsoft Corporation. All rights reserved. Microsoft, Windows, 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.

HP ConvergedSystem 300 for Microsoft Analytics Platform
Microsoft Analytics Platform System 4/16/2017 HP ConvergedSystem 300 for Microsoft Analytics Platform 2 x ProCurve 2810/48G switches Active server with control node and management node functionality Two servers and one optional passive spare server available FDR Infiniband Active Scale Unit Active scale unit 2 active server blocks 1 storage block (1, 2, or 3 terabytes) Base scale unit (minimum order) 1 rack block 2 passive server blocks 1 storage block PDU Active Scale Unit Active Scale Unit Active Scale Unit Base Scale Unit © 2014 Microsoft Corporation. All rights reserved. Microsoft, Windows, 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.

PDW scale from a quarter rack to multiple racks
Microsoft Analytics Platform System 4/16/2017 PDW scale from a quarter rack to multiple racks HP racks Base Active Compute Capacity increase Spare Total Raw disk: 1 TB Raw disk: 3 TB Capacity (TB) 1/4 1 2 N/A 4 15.1 45.3 53–227 1/2 100% 6 30.2 90.6 106–453 3/4 50% 8 135.9 159–680 3 33% 10 60.4 181.2 211–906 1 1/4 25% 13 75.5 226.5 264–1133 1 1/2 12 20% 15 271.8 317–1359 16 19 120.8 362.4 423–1812 2 1/2 7 20 24 151 453 529–2265 9 28 543.6 634–2718 32 37 241.6 724.8 846–3624 5 40 46 302 906 1057–4530 18 48 55 1087.2 1268–5436 21 56 17% 64 422.8 1268.4 1480–6342 © 2014 Microsoft Corporation. All rights reserved. Microsoft, Windows, 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.

4/16/2017 Microsoft Analytics Platform System No-compromise modern data warehouse solution Meeting today’s Big Data analytics requirements The modern data warehouse Enterprise-ready Hadoop with HDInsight and the simplicity of PolyBase Enterprise-ready Big Data Optimized performance with MPP technology and In-Memory Columnstore Performance at scale Providing value with a low TCO Optimal value © 2014 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries.

Please evaluate this session
4/16/2017 5:47 PM Please evaluate this session Your feedback is important to us! Visit Myignite at or download and use the Ignite Mobile App with the QR code above. © 2014 Microsoft Corporation. All rights reserved. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

Microsoft Ignite /16/2017 5:47 PM

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