What is Data Ware Housing? Types of Data Ware Housing

Data ware housing (DWH) is a collection of corporate information and data derived from operational systems and external data sources. A data warehouse is designed to support business decisions by allowing data consolidation, analysis and reporting at different aggregate levels. Data is populated into the DW through the processes of extraction, transformation and loading.

It is electronic storage of a large amount of information by a business which is designed for query and analysis instead of transaction processing. It is a process of transforming data into information and making it available to users in a timely manner.

Types of Data ware housing

Three main types of Data ware housing are

1. Enterprise Data Warehouse: Enterprise Data Warehouse is a centralized warehouse. It provides decision support service across the enterprise. It offers a unified approach for organizing and representing data. It also provide the ability to classify data according to the subject and give access according to those divisions.

2. Operational Data Store: Operational Data Store, which is also called ODS, are nothing but data store required when neither Data warehouse nor OLTP systems support organizations reporting needs. In ODS, Data warehouse is refreshed in real time. Hence, it is widely preferred for routine activities like storing records of the Employees.

3. Data Mart: It is a subset of the data warehouse. It specially designed for a particular line of business, such as sales, finance, sales or finance. In an independent data mart, data can collect directly from sources.

Advantages of Data Warehouse

  • Data warehouse allows business users to quickly access critical data from some sources all in one place.
  • Data warehouse provides consistent information on various cross-functional activities. It is also supporting ad-hoc reporting and query.
  • Data Warehouse helps to integrate many sources of data to reduce stress on the production system.
  • Integration make it easier for the user to use for reporting and analysis.
  • Data warehouse allows users to access critical data from the number of sources in a single place. Therefore, it saves user’s time of retrieving data from multiple sources.
  • Data warehouse stores a large amount of historical data. This helps users to analyze different time periods and trends to make future predictions.

Disadvantages of Data ware housing

  • No ideal option for unstructured data.
  • Creation and Implementation of Data Warehouse is time consuming effort.
  • Data Warehouse can be outdated relatively quickly.
  • Difficult to make changes in data types and ranges, data source schema, indexes, and queries.
  • The data warehouse may seem easy, but actually, it is too complex for the average users.
  • Sometime warehouse users will develop different business rules.
  • Organisations need to spend lots of their resources for training and Implementation purpose.