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Seminar on olap online analytical
- 1. Seminar on OLAP-online analytical processing By Hareesh Babu M S 14GAMT4004
- 2. Contents • Major featuresand functions • General features • Dimensional analysis • OLAP models • The MOLAP • The ROLAP • The implementation considerations
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- 4. Dimensional analysis • STARschema has three business dimensions, namely, product, time, and store. • Schema shows three-dimensional representation of the model. • AS a cube, with products on the X-axis, time on the Y-axis, and stores on the Z-axis.
- 5. A simple starschema represents dimensional analysis
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- 7. Queries and resultdisplay.
- 8. Uses and benefitsof olap • Increased productivity-of business managers, executives and analysts • Inherent flexibility- users can run their own analysis without it assistance • Benefits for IT developers- because using s/w specially designed for the system development results in faster delivery of application • Self sufficiency of users resulting in reduction backlog • faster delivery of applications following from the previous benefits. • More efficient operations through reducing time on query executions and in network traffic • Ability to model real-world challenges with business metrics and dimensions
- 9. OLAP MODELS There arethree type of OLAP models • ROLAP- stands for relational online analytical processing • MOLA- stands for multidimensional online analytical processing. • DOLAP- stands for desktop online analytical processing.
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- 11. • the threelayers in the multitier architecture. Precalculated and prefabricated multidimensional data cubes are stored in multidimensional databases. • The MOLAP engine in the application layer pushes a multidimensional view of the data from the MDDBs to the users.
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- 13. • the ROLAPmodel, data is stored as rows and columns in relational form. This model presents data to the users in the form of business dimensions. • The analytical server in the middle tier application layer creates multidimensional views on the fly • The multidimensional system at the presentation layer provides a multidimensional view of the data to the users
- 14. ROLAP has threedistinct characteristics • Supports all the basic OLAP basic features and functions. • Stores the data in relational form. • Supports dome form of aggregation.
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- 16. The implementation considerations •There are two main key issues considerations regard to the MOLAP model running under MDDBMS. a) The first issue relates to the lack of standardization. Each vendor tool has its own client interface. b) Another issue is scalability.
- 17. Data design andpreparation • In order to help prepare the data for the OLAP system we have to consider these characteristics • An OLAP system stores and uses much less data compared to a data warehouse • Data in the OLAP system is summarized. You will rarely find data at the lowest level of detail as in the data warehouse. • OLAP data is more flexible for processing and analysis partly because there is much less data to work with.
- 18. OLAP TOOLS Selection criteriafor selecting olap tools and products • Multidimensional representation of data. • Aggregation, summarization, precalculation, and derivations. • Formulas and complex calculations in an extensive library. • Cross-dimensional calculations • Time intelligence such as year-to-date, current and past fiscal periods, moving averages, • and moving totals. • Pivoting, cross-tabs, drill-down, and roll-up along single or multiple dimensions. • Interface of OLAP with applications and software such as spreadsheets, proprietary • client tools, third-party tools, and 4GL environments.
- 19. Implementation steps • Dimensionalmodelling. • Design and building of the MDDB. • Selection of the data to be moved into the OLAP system. • Data acquisition or extraction for the OLAP system. • Data loading into the OLAP server. • Computation of data aggregation and derived data • Implementation of application on the desktop • Provision of user training
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