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SQL 2012 & The Ultimate BI Suite. Efi Goldman Solution Expert at Panorama Software. Training Plan. Agenda. Business Logic Creating and Managing a Tabular Model – Demo How should I build my model? Advanced Analytics with Necto – Demo . Last Session Summery.
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SQL 2012 & The Ultimate BI Suite Efi Goldman Solution Expert at Panorama Software
Agenda • Business Logic • Creating and Managing a Tabular Model – Demo • How should I build my model? • Advanced Analytics with Necto – Demo
Last Session Summery • Three Main licensing Programs: • Standard (without Tabular Model) • BI Server (With Tabular Model and wide sharepoint integration) • Enterprise – Mission critical high performance • Two Visual Studio (BIDS) project types in Denali • Multidimensional project – with MDX and MOLAP/ROLAP • Tabular project – with DAX and VertiPaq/ DirectQuery • Two different Instances
VertiPaq for high performance, MOLAP for mission critical scale DirectQuery and ROLAP for real-time access to data sources State-of-the-art compression algorithms Scales to largest enterprise servers BI Semantic Model • Rich data modeling capabilities • Sophisticated business logic using MDX and DAX • Fine-grained security – row/cell level • Enterprise capabilities – multi-language and perspectives • Multi-dimensional and tabular modeling experiences • MDX and DAX for business logic and queries • Cached and passthrough storage modes • Choice of end-user BI tools Flexibility Richness Scalability
How Should I Build my Model? • Depends on the application needs for each layer • Data model • Business logic • Data access & storage
Data Model Tabular • Familiar model, easier to build, faster time to solution • Advanced concepts (parent-child, many-to-many) not available natively in the model… need calculations to simulate these • Easy to wrap a model over a raw database or warehouse for reporting & analytics Multidimensional • Sophisticated model, higher learning curve • Advanced concepts baked into the model and optimized (parent-child, many-to-many, attribute relationships, key vs. name, etc.) • Ideally suited for OLAP type apps (e.g. planning, budgeting, forecasting) that need the power of the multidimensional model
Business Logic DAX • Based on Excel formulas and relational concepts – easy to get started • Complex solutions require steeper learning curve – row/filter context, Calculate, etc. • Calculated columns enable new scenarios, however no named sets or calc members MDX • Based on understanding of multidimensional concepts – higher initial learning curve • Complex solutions require steeper learning curve – CurrentMember, overwrite semantics, etc. • Ideally suited for apps that need the power of multidimensional calculations – scopes, assignments, calc members
Data Access and Storage VertiPaq • In-memory column store… typical 10x compression • Brute force memory scans… high performance without tuning… • Basic paging … data volume mostly fits in physical memory MOLAP • Disk based store… typical 3x compression • Disk scans with in-memory subcube caching… aggregation, tuning required • Extensive I/O support… scales to multiple TBs DirectQuery • Passes through DAX queries & calculations… fully exploits backend database capabilities • No support for MDX queries… no support for data sources other than SQL Server (in Denali) ROLAP • Passes through fact table requests… not recommended for large dimension tables • Supports most relational data sources…
Denali demo
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