Data Warehouse Applications

Data Warehouse Applications

As discussed before, a data warehouse helps business executives to organize, analyze, and use their data for decision making. A data warehouse serves as a sole part of a plan-execute-assess “closed-loop” feedback system for the enterprise management. Data warehouses are widely used in the following fields:

  • Financial services
  • Banking services
  • Consumer goods
  • Retail sectors
  • Controlled manufacturing

Types of Data Warehouse

Information processing, analytical processing, and data mining are the three types of data warehouse applications that are discussed below:

  • Information Processing – A data warehouse allows to process the data stored in it. The data can be processed by means of querying, basic statistical analysis, reporting using crosstabs, tables, charts, or graphs.
  • Analytical Processing – A data warehouse supports analytical processing of the information stored in it. The data can be analyzed by means of basic OLAP operations, including slice-and-dice, drill down, drill up, and pivoting.
  • Data Mining – Data mining supports knowledge discovery by finding hidden patterns and associations, constructing analytical models, performing classification and prediction. These mining results can be presented using the visualization tools.
Sr.No. Data Warehouse (OLAP) Operational Database(OLTP)
1 It involves historical processing of information. It involves day-to-day processing.
2 OLAP systems are used by knowledge workers such as executives, managers, and analysts. OLTP systems are used by clerks, DBAs, or database professionals.
3 It is used to analyze the business. It is used to run the business.
4 It focuses on Information out. It focuses on Data in.
5 It is based on Star Schema, Snowflake Schema, and Fact Constellation Schema. It is based on Entity Relationship Model.
6 It focuses on Information out. It is application oriented.
7 It contains historical data. It contains current data.
8 It provides summarized and consolidated data. It provides primitive and highly detailed data.
9 It provides summarized and multidimensional view of data. It provides detailed and flat relational view of data.
10 The number of users is in hundreds. The number of users is in thousands.
11 The number of records accessed is in millions. The number of records accessed is in tens.
12 The database size is from 100GB to 100 TB. The database size is from 100 MB to 100 GB.
13 These are highly flexible. It provides high performance.