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Olap, expert system, data visualisation
This document provides an overview of OLAP (Online Analytical Processing). It discusses OLAP cubes, which allow fast analysis of data by arranging it into cubes that overcome limitations of relational databases. It also describes common OLAP operations like slice, dice, drill-down/up, roll-up, and pivot. Finally, it outlines benefits of OLAP like consistency of information and the ability to easily analyze data in broad or specific terms.
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Olap, expert system, data visualisation
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- 3. OVERVIEW INTRODUCTION OLAPCUBE OLAP OPERATION TYPES OF OLAP BENEFITS OF OLAP
- 4. 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. OLAP data is stored in multidimensional databases.
- 5. Some popularOLAP 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.
- 6. THE 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. It consists of numeric facts called measures which are categorized by dimensions. The OLAP cube consists of numeric facts called measures which are categorized by dimensions.
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- 8. OLAP OPERATIONS Theuser-initiated process of navigating by calling for page displays interactively, through the specification of slices via rotations and drill down/up is sometimes called "slice and dice". Slice: A slice is a subset of a multi-dimensional array corresponding to a single value for one or more members of the dimensions not in the subset. Dice: The dice operation is a slice on more than two dimensions of a data cube (or more than two consecutive slices).
- 9. Drill Down/Up:Drilling down or up is a specific analytical technique whereby the user navigates among levels of data ranging from the most summarized (up) to the most detailed (down). Roll-up: A roll-up involves computing all of the data relationships for one or more dimensions. To do this, a computational relationship or formula might be defined. Pivot: To change the dimensional orientation of a report or page display. The output of an OLAP query is typically displayed in a matrix (or pivot) format. The dimensions form the row and column of the matrix; the measures, the values.
- 10. TYPES OF OLAP Relational OLAP(ROLAP): Extended RDBMS with multidimensional data mapping to standard relational operation. Multidimensional OLAP(MOLAP): Implemented operation in multidimensional data. Hybrid OnlineAnalytical Processing (HOLAP) is a hybrid approach to the solution where the aggregated totals are stored in a multidimensional database while thedetail data is stored in the relational database. This is the balance between the data efficiency of the ROLAP model and the performance of the MOLAP model.
- 11. BENEFITS OF OLAP One main benefit of OLAP is consistency of information and calculations. "What if" scenarios are some of the most popular uses of OLAP software and are made eminently more possible by multidimensional processing. 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.
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- 13. Overview •What is anExpert System? •History •Components of Expert System •Who is involved? •Development of Expert System
- 14. WHAT IS ANEXPERT SYSTEM? An expert system is a computer program that contains some of the subject-specific knowledge of one or more human experts.
- 15. History of ExpertSystems
- 16. Early 70s Goal of AI scientists develop computer programs that could in some sense think . In 60s general purpose programs were developed for solving the classes of problems but this strategy produced no breakthroughs. In 1970 it was realized that The problem-solving power of program comes from the knowledge it possesses.
- 17. To make aprogram intelligent, provide it with lots of high-quality, specific knowledge about some problem area.
- 18. Building Blocks ofExpert System
- 19. Knowledge base(facts) Production Rules ("if.., then..") Inference Engine (controls how "if.., then.." rules are applied towards facts) User Interface
- 20. Knowledge Base Thecomponent of an expert system that contains the system’s knowledge. Expert systems are also known as Knowledge-based systems.
- 21. Knowledge Representation Knowledgeis represented in a computer in the form of rules ( Production rule). Consists of an IF part and THEN part. IF part lists a set of conditions in some logical combination. If the IF part of the rule is satisfied; consequently, the THEN part can be concluded.
- 22. Knowledge Representation Ifflammable liquid was spilled then call the fire department. If the material is acid and smells like vinegar then the spill material is acetic acid.
- 23. Chaining ofIF-THEN rules to form a line of reasoning Forward chaining (facts driven) Backward chaining (goal driven)
- 24. Inference Engine Aninference engine tries to derive answers from a knowledge base. It is the brain of the expert systems that provides a methodology for reasoning about the information in the knowledge base, and for formulating conclusions.
- 25. User Interface Itenables the user to communicate with an expert system.
- 26. Other features Reasoningwith uncertainty Explanation of the line of reasoning Fuzzy Logic
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- 28. Data Visualization “...to conveyinformation through visual representations.” “...produces (interactive) visual representations of abstract data to reinforce human cognition; thus enabling the viewer to gain knowledge about the internal structure of the data and causal relationships in it.”
- 29. Visualization Goals Answerquestions (or discover them) Make decisions See data in context Support graphical calculation Find patterns Present argument or tell a story Inspire
- 30. Three Functions of Visualization Record: store information Analyze: support reasoning about information Communicate: convey information to others