HANA and the Semantic Layer Support of HANA by the Semantic Layer via Relational Universes New BI4 Universe format (UNX) via a JDBC or ODBC relational connection Access to Tables (row or column store) and SQL views Access to Analytic and Calculation Views New SQL features in HANA are immediately available for universes Universes do not store data from HANA or add any performance overhead Universes are just a translation layer Universes are just like any other client tool using SQL to access HANA The latest data from HANA is sent to the client tool on query refresh
Business answers can be spread over several HANA views What do I want to do
Product Product Geography Geography Time Time Time Time Product Actual Actual Planned Planned Actual
• I can choose any object that will help to answer my business question • I don’t know the content of each view and I can mix objects that are not common to the selected views • I can specify which view(s) I want to use • I can filter my query • I can see the result in a single table/chart whenever possible • I can create as many queries as I want
Solution: Use Universes with HANA views for flexible reporting Leverage the Semantic Layer for flexible ad-hoc query Access multiple HANA Views and synchronize the datasets locally without impacting performance. Use advanced Universe features like contexts, aggregate awareness to navigate through HANA views seamlessly Create your Navigation Paths to enable drill-down analytical reporting in Information Design Tool
HANA Variables and Input Parameters HANA variables Are used to filter the content of an information model. They don’t impact the execution workflow of the information model and are applied to a query to filter out some values Applied to the where clause
Input Parameters Are used to manipulate the execution of the information model In SQL, parameters values are passed via the PLACEHOLDER reserved word
Index Awareness in IDT Helps create more efficient SQL The universe can substitute IDs for descriptions Primary and foreign keys must be programmed and must be done for every object to be made “index aware” Which is faster? Without Index Awareness With Index Awareness
SAP Web Intelligence Web Intelligence is an interactive reporting tool that can access relational as well as multidimensional datasources via the concept of Universes. The reports can be viewed online or offline thanks to the microcube, an embedded local in-memory cache engine (microcube). In case of Hana, WebI will access it through relational access using SQL,
• Enables off-line (microcube) as well as interactive analysis (e.g,HANA)
SAP Web Intelligence with SAP HANA Recommendations • Avoid querying high volume of detailed data • Push calculations down to HANA • Retrieve only the results the Webi report needs (Summary data) • Create reports on summary data with refresh on open • Let your users explore the data using drill actions in real-time
SAP Web Intelligence - Microcube Why Web Intelligence is using a microcube / local cube? The micro cube is mandatory and an important part of the Webi architecture design. Having a microcube has a lot advantages when designing and consuming a Web Intelligence reports, and it has been designed for a vast majority of databases. The main benefit is that it can offer offline analytical capabilities like report viewing, drilling, quick filtering, local calculations: The WebI calculation compensates missing data source expressiveness (cross table, multi-context evaluation, advanced functions like Previous, …) . It requires to fetch raw data first before performing local data processing It enables Multi-data Provider support, which requires local data materialization for data synchronization It enables data historization (if not available from the data source) which allows users to create data snapshots, and make features like Track Data Change possible.
Leverage the Semantic Layer for flexible ad-hoc query Access multiple HANA Views and synchronize the datasets locally. Use advanced Universe features like contexts and aggregate awareness to navigate through HANA views seamlessly Create your Navigation Paths to enable drill-down analytical reporting Use index awareness
Don’t Join HANA views in the data foundation
Optimize your Web Intelligence reports for HANA Make sure your report is HANA optimized by “stripping” your query. Push calculations down to HANA and retrieve only the results. Enable drill workflows to make the most of with SAP HANA performance.