Introduction to tabular models Welcome to Tabular Introduction to tabular models Dustin Ryan @SQLDusty

Who’s this guy? Dustin Ryan – Senior B.I. Consultant & Trainer at Pragmatic Works Data warehouse design, SSRS, SSIS, SSAS, SharePoint BI, Power BI Author, contributor, technical editor PASS Summit, SQL Rally, SQL Saturday, Code Camp My family, sleep, preparing for the war against the machines

Agenda Making the right choice Building a Tabular Model Best Practices Resources

SSAS showdown Cubes Tabular model

Yes (detail opens in separate worksheet) Feature parity Multidimensional Tabular Power Pivot Actions Yes No Aggregations Calculated Measures Custom Assemblies Custom Rollups Distinct Count Yes (via DAX) Drill through Yes (detail opens in separate worksheet) Hierarchies KPIs Linked objects Yes (linked tables) Many-to-many relationships Parent-child Hierarchies Partitions Perspectives Semi-additive Measures Translations User-defined Hierarchies Writeback

Considerations Scalability Performance Time to develop Complex business problems Learning curve

Scalability Tabular Multidimensional In-Memory Technology (x-Velocity) Can Store Large Amounts of Data No Aggregations. Column-Based Storage. Data Compression 10x Pre-Aggregated Data From Disk Can Store Very Large Amounts of Data Uses Aggregations to Increase Query Performance Data Compression 3x Devin Starts

Performance Tabular Multidimensional Generally Speaking Tabular will perform faster Tabular Engine Does Not Require a Great Deal of Performance Tuning Best at Returning Low Granularity Data Need memory optimized hardware Pre-Aggregated Data From Disk Can Store Very Large Amounts of Data Uses Aggregations to Increase Query Performance Often Faster Than Tabular When Pulling From Warm Cache Need storage optimized hardware Devin Starts

Time to Develop Tabular Multidimensional By Far Less Time to Develop Can Upgrade From Power Pivot Does Not Require Dimensional Model (But it’s still a good idea) Much Simpler Interface for Creating Model Long Planning and Development Cycles No Upgrade Path Requires Dimensional Model Devin Starts

Complex Business problems Tabular Multidimensional Can Handle Complex Relationships with DAX Has Built-in Capabilities for Complex Relationships Role Playing Parent-Child Many-to-many Devin Starts

Learning Curve Tabular Multidimensional Uses DAX (Data Analysis Expressions) for Query Language If You Know Excel Formulas Then DAX Will Be Easy Simple Drag and Drop KPI Creation Relationships are simple (no composite keys) Uses MDX (Multi-Dimensional Expressions) for Query Language Difficult to Learn but has Benefits (Navigating Hierarchies) More Complex KPI Creation Multiple relationship types Devin Starts

Other considerations After you Choose… There is No Migration Path to the Other Technology Tabular Best on its Own Machine, Not a Good Candidate for a Shared Service due to differences in hardware requirements Devin Starts

The Bottom line Consider Tabular… Consider Multidimensional… If You Have a Short Development Timeline If You are Working with a Plethora of Memory If You Data Model is Simple If You Have Many Disparate Data Sources If Users Need to Query Large Amounts of Detail Data Consider Multidimensional… If You are Using SQL Server 2008 R2 or Earlier If You Have a Multi-Terabyte Data Source If You Have a Complex Data Model If You Need Multidimensional only features (Actions, Data Mining, Writeback, Translations) Devin Starts

To the Tabular Model! Devin Starts

Resources SQL Server 2012 Analysis Services The BISM Tabular Model (link) Practical PowerPivot & DAX Formulas for Excel 2010 (link) Performance Tuning of Tabular Models in SQL Server 2012 Analysis Services Whitepaper (link) Devin Starts

Thanks for attending my session! Contact Me @SQLDusty (link) dryan@Pragmaticworks.com (link) Thanks for attending my session! Devin Starts