OLAP
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Online analytical processing (OLAP) allows users to easily extract and analyze data from different perspectives. It originated in the 1970s and was formalized in 1993, with OLAP cubes organizing numeric facts by dimensions to enable fast analysis. OLAP provides operations like roll-up, drill-down, slice, and dice to analyze aggregated data across multiple systems. It offers advantages over relational databases for consistent reporting and analysis.
![ROLL UP
• Takes the current aggregation level of fact values
and does a further aggregation on one or more of
the dimensions.
• Equivalent to doing GROUP BY to this dimension by
using attribute hierarchy.
SELECT [attribute list], SUM [attribute names]
FROM [table list]
WHERE [condition list]
GROUP BY [grouping list];](https://image.slidesharecdn.com/group3-151213105817/85/OLAP-11-320.jpg)
OLAP
- 2. OVERVIEW • INTRODUCTION • HISTORY OF OLAP • OLAP CUBE • DIFFERENCE BETWEEN OLAP & OLTP • OLAP OPERATIONS • ADVANTAGES & DISADVANTAGES
- 3. INTRODUCTION TO OLAP • OLAP (online analytical processing) is computer processing that enables a user to easily and selectively extract and view data from different points of view. • OLAP allows users to analyze database information from multiple database systems at one time.
- 4. HISTORY • In 1993, E. F. Codd came up with the term online analytical processing (OLAP) and proposed 12 criteria to define an OLAP database • The term OLAP seems perfect to describe databases designed to facilitate decision making (analysis) in an organization • The first product that performed OLAP queries was Express, which was released in 1970 (and acquired by Oracle in 1995 from Information Resources).
- 5. Some popular OLAP server software programs include: Oracle Express Server Hyperion Solutions Essbase OLAP processing is often used for data mining. OLAP products are typically designed for multiple- user environments, with the cost of the software based on the number of users.
- 7. OLAP CUBE • An OLAP Cube is a data structure that allows fast analysis of data. • The arrangement of data into cubes overcomes a limitation of relational databases. • The OLAP cube consists of numeric facts called measures which are categorized by dimensions.
- 8. OLAP CUBE
- 9. OLTP VS OLAP • Source of data • Purpose of data • Queries • Processing speed • Space Requirement • Database Design • Backup and Recovery
- 10. OPERATIONS OF OLAP • There are different kind of operations which we can perform in OLAP • Roll up • Drill Down • Slice • Dice • Pivot • Drill-across • Drill-through
- 11. ROLL UP • Takes the current aggregation level of fact values and does a further aggregation on one or more of the dimensions. • Equivalent to doing GROUP BY to this dimension by using attribute hierarchy. SELECT [attribute list], SUM [attribute names] FROM [table list] WHERE [condition list] GROUP BY [grouping list];
- 12. DRILL DOWN • Summarizes data at a lower level of a dimension hierarchy. • Increases a number of dimensions - adds new headers
- 13. SLICE Performs a selection on one dimension of the given cube. Sets one or more dimensions to specific values and keeps a subset of dimensions for selected values.
- 14. DICE Define a sub-cube by performing a selection of one or more dimensions. Refers to range select condition on one dimension, or to select condition on more than one dimension. Reduces the number of member values of one or more dimensions.
- 15. PIVOT • Rotates the data axis to view the data from different perspectives. • Groups data with different dimensions.
- 16. DRILL-ACROSS AND DRILL- THROUGH Drill-across : Accesses more than one fact table that is linked by common dimensions. Combines cubes that share one or more dimensions. •Drill-through: Drill down to the bottom level of a data cube down to its back-end relational tables.
- 18. ADVANTAGES • Consistency of Information and calculations • What if" scenarios • It allows a manager to pull down data from an OLAP database in broad or specific terms. • OLAP creates a single platform for all the information and business needs, planning, budgeting, forecasting, reporting and analysis
- 19. DISADVANTAGES • Pre-Modeling • Great Dependence on IT • Slow In Reacting
- 20. PURPOSE OF OLAP • To derive summarized information from large volume database • To generate automated reports for human view
- 21. CONCLUSION • OLAP is a significant improvement over query systems • OLAP is an interactive system to show different summaries of multidimensional data by interactively selecting the attributes in a multidimensional data cube
- 22. REFERENCES • http://www.skybuffer.com/blog/1/ • https:// en.wikipedia.org/wiki/Online_analytical_processing • http:// searchdatamanagement.techtarget.com/definition/O LAP • http://olap.com/olap-definition/ • https://support.office.com/en-my/article/Overview-of- Online-Analytical-Processing-OLAP-15d2cdde-f70b- 4277-b009-ed732b75fdd6