Modeling and Analytics Features Coming in Analysis Services vNext Christian Wade, Senior Program Manager

Microsoft BI Platform DATA Model Analyze & author Deliver Visualize Power BI Power BI Azure Analysis Services Web Embedded in your apps Mobile Cloud On –premises data gateway On-premises Key points: Azure Analysis Services, is based on the proven analytical engine in SQL Server 2016 Analysis Services. Customers can access data sources across on-premises and the cloud, model that data, and provide business users with a simplified view of their data to enable interactive self-service BI and data discovery using their preferred data visualization tool. Easy to deploy, scale, and manage as a platform-as-a-service solution Create a provision an Azure Analysis Service server in seconds. Elastic scale to move up and down with your business needs. Reduce the burden of managing infrastructure with a fully managed Analysis Services in the cloud.   Integrate data from anywhere. Build your semantic model from modern data sources like Azure SQL Database and Azure SQL DW as well as on-prem data like SQL Server 2016 Connect to your semantic model with your favorite BI visualization tool and interact with data at scale and the speed. SQL Server Analysis Services SQL Server Reporting Services Excel Power BI Desktop

SQL Server 2016 Analysis Services – what’s new 9/20/2018 Analysis Services Enterprise scale models with in-memory technology built-in Increase adoption Use Analysis Services as a Semantic Model Combine data from many places and apply business rules Scalability for interactive analysis “at the speed of thought” Integration with DevOps Easily create models IT pro BI consumers Faster time to insight Organizations have lots of data, but difficult to access. BI Semantic model unlocks that data for business users. Contains business logic, sophisticated calculations High reusability for consistent decisions in an enterprise org Reuse in enterprise org Scalability IT owned & managed Business analyst Share insights faster © 2016 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.

SQL Server Analysis Services Visualizations & insights Power BI On-prem data sources Authoring & Dev Key points SQL Server Analysis Services is typically used by organization today for their on premises BI solution. It allows them to connect to their on-prem data sources a turn complex data into a trusted, single source of truth. Then visualize and gain insights from their data with SSRS or Power BI or other 3rd party visualization & reporting tools. There are many new capabilities in SQL Server 2016 Analysis Services including: Enhance performance with parallel partition processing Over 50 new DAX functions Ability to view semantic models in a preferred language Role level security Support for more data sources like Oracle and Teradata Etc., Excel DirectQuery SQL Server Cached Model Visual Studio SQL Server Reporting Services SQL Server Analysis Services Other data sources SSMS Other 3rd party tools & services

Azure Analysis Services Cloud data sources Visualizations & insights SQL Database DirectQuery Power BI Cached Model SQL Data Warehouse On-prem data sources Authoring & Dev Key points Azure Analysis Services provides the same enterprise-grade data modeling in the cloud. Fully managed PaaS. It’s built on the proven analytics engine in Microsoft SQL Server 2016 Analysis Services. So all that same functionality and capability now applies to the cloud service Additionally it enables new scenarios like: Freeing up managing infrastructure & scale your data models with your cloud data sources. Whether new or existing models. Take advantage of Azure to easily scale up to handle increased demand from your BI user Leverage the same tools like SQL Server Management Studio (SSMS) to mange your BI models in the cloud. … Excel DirectQuery SQL Server Cached Model Visual Studio SQL Server Reporting Services Other data sources SSMS Other 3rd party tools & services

9/20/2018 8:57 AM 1200 Compatibility Level Available in Azure Analysis Services & SQL Server 2016 Modeling and analytics Bi-directional cross filters Calculated tables Display folders Translations Over 50 new DAX functions DirectQuery enhancements Manageability Tabular Object Model (TOM) Tabular Model Scripting Language (TMSL) Performance and scalability Parallel partition processing NUMA awareness and memory allocator (SP1) Super DAX Developer Tools Tabular Model Explorer Integrated workspace server DAX formula editing Modeling and analytics Bi-directional cross filters Many-to-many dimension scenarios without need to write complex DAX formulas For whole table, not just a measure Various use cases such as account balance, currency conversion, distinct count of attributes Calculated tables Dynamically generate a table based on a DAX formula. Various use cases including role-playing dimensions Some performance improvements available Display folders Present model elements and measures by business function in Pivot Tables and in Power BI Translations DirectQuery enhancements Data is up to date with no management of loading the in-memory cache Big data sets that don’t fit into memory New data sources: APS / SQL DW, Oracle, Teradata Support for MDX queries (Pivot Tables) Improved query generation resulting in faster performance Row-level security defined with DAX filters Over 50 new DAX functions DATEDIFF, SELECTCOLUMNS, SUMMARIZECOLUMNS, CROSSFILTER Manageability Tabular Object Model (TOM) Tables, columns, relationships – not cubes, measure groups, dimensions Tabular Model Scripting Language (TMSL) JSON representation of TOM – with commands for manageability such as create/alter database, backup, restore, attach, detach Performance and scalability NUMA awareness and memory allocator The in-memory engine in SP1 maintains a separate job queue on each NUMA node The Intel TBB-based scalable allocator that provides separate memory pools for every core. As the number of cores increases, the system can scale almost linearly Parallel partition processing Super DAX Strict evaluation of IF/SWITCH, Variables Some cases just restoring a 2014 model to 2016 provides significant DAX performance benefits © 2014 Microsoft Corporation. All rights reserved. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

9/20/2018 8:57 AM 1400 Compatibility Level Coming soon in Azure Analysis Services & SQL Server 2017 Data connectivity Rich set of data sources Data transformations and mashups with Power Query Formula Language Modeling and analytics Detail Rows Enhanced support for ragged hierarchies Enhanced time intelligence Object level security Developer tools SSDT for VS 2017 DAX Editor for SSDT and SSMS © 2014 Microsoft Corporation. All rights reserved. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

Demo Roadmap (NDA) 2nd Quarter GA (with GA pricing) April B2B support Backup and Restore Smaller SKUs May Power Query / 1400 Models Large SKUs July Unified Gateway ISV feature for small model eviction August Scale out