Data warehousing data mining and olap

  • Data mining books

    OLAP capability, as embodied by a data warehouse, goes beyond simple querying and reporting.
    It involves the integration of the numerous enterprise source systems into a large historical dataset which can be processed with advanced queries..

  • How data warehousing and OLAP related to data mining?

    Data warehouses provide on-line analytical processing (OLAP) tools for the interactive analysis of multidimensional data of varied granularities, which facilitates effective data mining..

  • How does OLAP work in data warehouse?

    OLAP works by extracting data from multiple sources and formatting it into cubes, which can then be analyzed from multiple points of view.
    Multiple cubes can be nested, creating multidimensional "hypercubes.".

  • What is data warehousing and mining?

    Data warehousing is a method of organizing and compiling data into one database, whereas data mining deals with fetching important data from databases.
    Data mining attempts to depict meaningful patterns through a dependency on the data that is compiled in the data warehouse..

  • What is difference between data warehousing and data mining?

    Data warehousing refers to a typical procedure of compiling and organising data into a common database.
    On the other hand, data mining basically refers to the process of extracting useful data from various databases..

  • What is OLAP in data warehousing and data mining?

    An online analytical processing (OLAP) system works by collecting, organizing, aggregating, and analyzing data using the following steps: The OLAP server collects data from multiple data sources, including relational databases and data warehouses..

  • When to use OLAP vs.
    OLTP.
    Online analytical processing (OLAP) and online transaction processing (OLTP) are two different data processing systems designed for different purposes.
    OLAP is optimized for complex data analysis and reporting, while OLTP is optimized for transactional processing and real-time updates.
Data warehouse is an archive where historical corporate data is stored and can be analyzed then. It can use different technologies for data extraction and analyzing. And OLAP is one of those technologies that analyze and evaluate data from the data warehouse.
Nov 22, 2021It can be used to analyze summarized and detailed information, where the results are displayed in the form of documents and charts. Later, the 
This reference provides strategic, theoretical and practical insight into three information management technologies: data warehousing, online analytical processing (OLAP), and data mining. It shows how these technologies can work together to Google BooksOriginally published: 1997Author: Alex Berson

What is covered in data warehouse design & OLAP?

It comprehensively covers data warehouse design (using various approaches, models and indexing techniques), relational data base mining, data warehousing on the Web, and data replication

Several chapters discuss application development with popular OLAP tools

Some of these items are dispatched sooner than the others

What is data warehousing & on-line analytical processing (OLAP)?

Data warehousing and on-line analytical processing (OLAP) are essential elements of decision support, which has increasingly become a focus of the database industry

Many commercial products and services are now available, and all of the principal database management system vendors now have offerings in these areas

What is OLAP data mining?

They are built for speed and efficiency to keep the company’s day-to-day operations moving fast, unlike data warehouses, which runs very slowly

This is where OLAP (On Line Analytical Processing) introduces the tools to analyze data warehouse information

We need data mining to collect data and to analyze it, or if not analyzed, collected


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