ssas tabular vs multidimensional performance

#Ssas tabular vs multidimensional performance how to

Choosing to ignore them, doesn’t mean they go away. They may not feel right as they are different from OLTP, but like the laws of gravity, they just “are”. Optimized Query Performance Modeling best practices have been established over time. A cube designed with 3NF dimensions is not scalable! A solid OLAP data model is a hill worth dying upon. The current cube design should be able to scale to many more measure groups and shared dimensions. This isn’t just about number of rows, but growth in additional attributes and measures.

Modeling for BI Return on Investment! Data Integrity Data Warehouse Design Scalability Optimized Query Performance Uncluttered GUI Cube Design Scalability As your business grows, the cubes should grow. 5 Azure Power BI or SharePoint Services One time configuration by your SharePoint Administrator 4 SharePoint, O-365 & SSAS Security Coordinated with Active Directory, roles and groups 3 SQL Server Analysis Services (SSAS) Deployed Multidimensional Cubes or Tabular Models 2 SQL Server Data Warehouse Star schema EDW (Enterprise Data Warehouse) 1 Information Data Store (IDS) Consolidated and cleansed 3NF data warehouse Take time to build a strong foundation!īI Blueprint Reporting Sources Data model considerationsĩ Data Warehouse Design Scalability Optimized Query Performance Reporting Components Business Intelligence Components 6 Reporting Initiated by your development team and grown through self-service BI. Talking Points: If you have not defined a single report, how will your end result be optimized for reporting? How do we frequently sacrifice the permanent, R&A, on the alter of the immediate, a faster ETL? Related tables only show up when connected to a MultiD cube. Pivot tables also does not show related tables in a tabular models. Excel: Designed originally to interface with MultiD and some terminology remains, like asking you to connect to a “cube” tabular model, which does not exist. An absolute must-have for trouble shooting long-running queries.

#Ssas tabular vs multidimensional performance how to

Not necessarily a “property”, but support for parent-child relationships have still not shown up in tabular! Storage and query engines: Tabular is not a cube, and a cube is not a worksheet! Data volumes and cardinality are key critical when deciding to go MultiD vs Tabular Performance Tuning: We all come back to Extended Events, so just understand what performance indicators to select when dealing with one or the other and know how to read them. Some are truly frustrating, like the inability to show NULL when a user selects a measure group not related to a chosen dimension, or the ability to disable the Model.bim file forcing users through a perspective. Properties: Are extremely limited in tabular when compared to MultiD. Also the ability to create usage-based aggregations is a key MultiD benefit. Attribute Relationships: Do not exist in tabular, but give MultiD many advantages, among others, the ability to join dimensions and facts of different granularity Aggregations: Do not exist in tabular, but give MultiD a huge performance boost. For tabular, primarily an end-user drill down convenience. Hierarchies: A performance boom for MultiD. MDX vs DAX: This doesn’t require much discuss except to say that it is a strong tabular model benefit as it can be more easily understood by non-technical personnel Role Playing Dimension: Also a SQL 2016 tabular improvement, but these definitely work differently between MultiD and tabular. Date Calculations: Much more flexible, but development intensive in tabular.

The Bridge table is the critical success point in both models. Many-to-many: Now supported in SQL 2016 tabular models Drill across: Should now be able to work in both since M-to-M is now supported. Belong is an extremely brief recap of our conversation. In other words, you SOMETIMES can get a similar output with both tabular and MultiD, but there are subtle differences. Talking Points The Big BI Picture Many-to-Many Relationships Role Playing Dimensions Hierarchies Tables of Different Granularity Security, Perspectives & Partitions Drill Across Deployment & Processing Options Performance Optimization Auditing Key Property Differences Power BI GUI Demo These were talking points for our meeting on October 6th, These items reflect differences between MultiD and tabular that aren’t often discussed with a focus on both Visual Studio development and end-user experience. SSAS 2016 Beyond the Basics of MultiD vs Tabular in SQL 2016 All function reference  SQL 2016 new functions  Presentation on theme: 'Example of a page header'- Presentation transcript: