Data Analysis And Olap Pdf

data analysis and olap pdf

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OLAP tools enable users to analyze multidimensional data interactively from multiple perspectives.

Online Analytical Processing, a category of software tools which provide analysis of data for business decisions. OLAP systems allow users to analyze database information from multiple database systems at one time. The primary objective is data analysis and not data processing.

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Online analytical processing

Skip to Main Content. A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity. Use of this web site signifies your agreement to the terms and conditions.

Reverse engineering meets data analysis Abstract: We demonstrate how the data management techniques known as On-Line Analytical Processing, or OLAP, can be used to enhance the sophistication and range of software reverse engineering tools. This is the first comprehensive examination of the similarities and differences in these tasks both in how OLAP techniques meet or fail to meet the needs of reverse engineering and in how reverse engineering can be recast using data analysis.

To permit the seamless integration of these technologies, we extend a multidimensional data model to manage dynamically changing dimensions over which data can be aggregated.

We use a case study of the Apache Web server to show how our solutions permit an integrated view of data, ranging from low level program analysis information to abstract, aggregate information. These high-level abstractions may be provided either by humans perhaps using a visualization tool or directly from reverse engineering tools or data mining techniques.

IWPC Article :. DOI: Need Help?

What is the definition of OLAP?

OLAP performs multidimensional analysis of business data and provides the capability for complex calculations, trend analysis, and sophisticated data modeling. OLAP enables end-users to perform ad hoc analysis of data in multiple dimensions, thereby providing the insight and understanding they need for better decision making. Knowledge is the foundation of all successful decisions. Successful businesses continuously plan, analyze and report on sales and operational activities in order to maximize efficiency, reduce expenditures and gain greater market share. Statisticians will tell you that the more sample data you have, the more likely the resulting statistic will be true. Naturally, the more data a company can access about a specific activity, the more likely that the plan to improve that activity will be effective. All businesses collect data using many different systems, and the challenge remains: how to get all the data together to create accurate, reliable, fast information about the business.

What is the definition of OLAP?

Skip to search form Skip to main content You are currently offline. Some features of the site may not work correctly. DOI: Conn Published Computer Science Proceedings. This paper elaborates on the justification and need for integration of OLTP online transaction processing and OLAP online analytical processing data environments for the purpose of real time data analysis, and reviews potential implementation methods and architectures for integration of these disparate environments.

Skip to Main Content. A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity. Use of this web site signifies your agreement to the terms and conditions. Reverse engineering meets data analysis Abstract: We demonstrate how the data management techniques known as On-Line Analytical Processing, or OLAP, can be used to enhance the sophistication and range of software reverse engineering tools.

OLTP vs OLAP: Difference Between OLTP and OLAP

Online Analytical Processing OLAP is a category of software that allows users to analyze information from multiple database systems at the same time. It is a technology that enables analysts to extract and view business data from different points of view. Analysts frequently need to group, aggregate and join data. These operations in relational databases are resource intensive. With OLAP data can be pre-calculated and pre-aggregated, making analysis faster. OLAP databases are divided into one or more cubes.

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