Data Warehousing

Data warehousing (DW) is a method of gathering and analyzing data from many sources in order to get useful business insights. Typically, a data warehouse is used to integrate and analyze corporate data from many sources. The data warehouse is the heart of the business intelligence (BI) system, which is designed to analyze and report on data.

It’s a collection of technology and components that helps with data strategy. It refers to a company’s electronic storage of a huge volume of data that is intended for inquiry and analysis rather than transaction processing. It is a method of converting data into information and making it available to people in a timely manner so that it can be used to make a difference.

Data warehouse system is also known by the following name:

  • Decision Support System (DSS)
  • Executive Information System
  • Management Information System
  • Business Intelligence Solution
  • Analytic Application
  • Data Warehouse

How Data warehouse works?

A Data Warehouse is a central repository where data from one or more data sources is stored. The transactional system and other relational databases feed data into a data warehouse.

Data may be:

  • Structured
  • Semi-structured
  • Unstructured data

Users can access the processed data in the Data Warehouse using Business Intelligence tools, SQL clients, and spreadsheets after the data has been processed, transformed, and ingested. A data warehouse combines data from various sources into a single, comprehensive database.

Types of Data Warehouse:

Three main types of Data Warehouses (DWH) are:

1. Enterprise Data Warehouse (EDW):

A centralized warehouse is an Enterprise Data Warehouse (EDW). It offers decision-making assistance to the entire company. It provides a unified approach to data organization and representation. It also has the capability of classifying data by subject and granting access based on such divisions.

2. Operational Data Store:

Operational Data Stores, or ODS, are simply data stores that are required when neither a data warehouse nor an OLTP system can meet an organization’s reporting needs. The data warehouse in ODS is updated in real time. As a result, it is extensively used for mundane tasks such as keeping employee details.

3. Data Mart:

The data warehouse is subdivided into data marts. It is tailored to a specific business line, such as sales, finance, sales, or finance. Data can be collected directly from sources in an independent data mart.

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