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Relational OLAP and Aggregate Navigators

Relational OLAP and Aggregate Navigators. Data Warehousing Lab. M.S. 2 Hyeyoung Cho. OLAP. OLAP(OnLine Analytical Processing) One technology for querying the warehouse Suited for summarizing and analyzing huge quantities of data 4 basic functions Multidimensionality Drill down

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Relational OLAP and Aggregate Navigators

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  1. Relational OLAP and Aggregate Navigators Data Warehousing Lab. M.S. 2 Hyeyoung Cho

  2. OLAP • OLAP(OnLine Analytical Processing) • One technology for querying the warehouse • Suited for summarizing and analyzing huge quantities of data • 4 basic functions • Multidimensionality • Drill down • Rotation • Multiple modes of view

  3. OLAP basic functions • Multidimensionality • provide data about performance measures, broken down by one or more dimensions • dimensions • combine to describe measures • vary according to industry, strategy, kinds of information that systems capture • filtered by dimension and/or measure value

  4. OLAP basic functions

  5. OLAP basic functions • Drill down • break a summary item into its detailed components • multiple parallel hierarchies • DATE dimension(year vs. seasonal year) both share a common atomic data element : day

  6. OLAP basic functions • view highly summarized data and then navigate down to less summarized data • drill across:drill down into a different dimension • rolling up:drill from a detail back up to a total

  7. OLAP basic functions • Rotation month on the Y-axis product on the X-axis rotation month on the X-axis product on the Y-axis

  8. OLAP basic functions • change view perspective • drill down and rotation

  9. OLAP basic functions • Multiple modes of view • View data in a variety of formats(graph,chart,etc.)

  10. OLAP database technologies • OLAP • application for querying and viewing data • regardless of how that data is stored • ROLAP and MOLAP • ROLAP (Relational OLAP) :RDB기반 • MOLAP (Multidimensional OLAP) :MDDB기반 • data marts • tuned for specific subject areas • more normalized than simple star schema

  11. OLAP database technologies • Cube(dataset to analyze) • three dimension : height,width,depth(dice) • Comprised of any number of dimensions

  12. MDDB • Array • RDB : store data in tables and columns • MDDB : store data in large multidimensional arrays • Multidimensional Database Vendors • Oracle Express Server(OES) • Essbase(Hyperion Software) • Powerplay(Cognos) • Gentia(Gentia Software) • Suitable for analyzing narrowly focused sets of data

  13. RDB • Aggregate Navigation • Oracle 8i ’s query rewrite capabilities • Materialized views in Oracle 8i • ease the construction and maintenance of the table • speed up query performance

  14. RDB • aggregate navigators • select the best table for each query • know which summaries exist and the size

  15. RDB • ROLAP Vs. Online Report Writing • support • Generate SQL calls, Format the results • not support • OLAP basic function, Aggregate navigation • ROLAP tool vendors • Oracle Discoverer • MicroStrategy DSS Agent, • Computer Associates DecisionBase

  16. ROLAP Vs.MOLAP • query performance • query response time • precalculate all combinations and summaries of data • three dimensions: • 1개의 3D atomic level array • 3개의 2D atomic level array • 3개의 1D summary array broken by each dimension

  17. ROLAP Vs.MOLAP

  18. ROLAP Vs.MOLAP • load performance • populate data structures and perform calculations time

  19. ROLAP Vs.MOLAP • Analytic capability

  20. ROLAP Vs.MOLAP • Dataset Sizes • Dimension Handling

  21. ROLAP Vs.MOLAP • Maintenance Effort

  22. ROLAP and MOLAP Harmony • Which technology wins? • relational database : a large, cross-functional, enterprise data warehouse • multidimensional database : a well-defined, highly targeted analysis-focused data mart limited dimensionality and little need for detailed, atomic-level data • A corporate data warehouse feeds smaller, narrowly focused or stand alone data marts → ROLAP and MOLAP are complementary!

  23. ROLAP and MOLAP Harmony • drill through • integrate ROLAP and MOLAP technologies • drill down in the MDDB until reach in the lowest level of detail • query to RDB that contains very detailed atomic-level data • not perfect yet so require the custom code each drill-through query

  24. Conclusion • OLAP is a user interface, not a data storage, concept • OLAP basic functions: multidimensionality, Drill down, Rotation, Multiple modes of view • ROLAP Vs. MOLAP • What is a best approach to OLAP?

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