Data warehousing is a method of assembling and handling data from various sources to give appropriate business insights. Data warehouses are electronic storage units which are used to store data which are already processed and helps in the decision making process of any business. Large amounts of data that are generated by a business are processed and stored in data warehouses and made available to the users when required. Organizational operation databases are stored separately. Data warehouse and operational database both are different. Using data warehouse aids in increasing performance and decreasing the response time.

TYPES OF DATA WAREHOUSE:

1. Enterprise Data Warehouse
   Enterprise data warehouse is a centralized warehouse which is used for storing business information from multiple sources. The information which is stored in it is made available across the organization, which can further be used for various purposes such as data analytics, etc. This type of data warehouse can be an organization’s prized possession. All the information related to business is stored in enterprise data warehouse.

2. Operational Data Store
   Operational data store is a centralized database which is used to store the current information. It assists business intelligence process by providing data which helps in decision making process and strategic planning. It does not store the outdated data; it stores latest data. Operational data stores are volatile as the information in it always is upgraded to new and current information.

3. Data Mart
   Data mart is a subset of a data warehouse. It is not the centralized database which store information about whole business instead it only store information about a particular unit or department of that particular organization. In data mart, the number of sources from which the data is taken is less as compared to the number of sources from which a data is taken in enterprise data warehouse. Data mart are flexible, fast and small in size.

APPLICATIONS ~  DATA WAREHOUSE:

1. Airlines
   In an airline system, frequent flyer program promotions, crew assignment are some of the tasks for which data warehouses are used.

2. Banking
   Data warehouses are used on a large scale in banking sector. It is used to manage resources efficiently. Market research, performance analysis are some of the areas where data warehouses are used in the banking sector.

3. Healthcare
   In the healthcare sector data warehouses are used to perform various tasks such as generate patient’s treatment report, share data with tie-in insurance companies, medical aid services etc.

4. Public Sector
   There are various tasks that public sector performs. Data warehouse assists public sector to maintain and analyze health record, tax records of every individual.

5. Investment and Insurance
   Analyzing data patterns, customer trends and to track market movement are some of the functions for which data warehouses are used in investment and insurance sector.

6. Hospitality Industry
   In hospitality industry, data warehouses are used to make an idea of their advertising and promotion campaign which helps them to target users based on their travel pattern.

ADVANTAGES OF DATA WAREHOUSING:

• It stores large amount of data which assists users to analyze the data and make based on the information gathered.
• It stores data from multiple sources at a single place which saves organization’s time to retrieve all data from multiple places.
• It allows quick access of critical data.

DISADVANTAGES OF DATA WAREHOUSING:

• For training and implementation purpose of data warehouses lots of resources of organization are used.
• It is not a best option for unstructured data
• It is difficult to make changes in data warehouse.
• It is very complex for average users.

CONCLUSION:

Data warehouses are very essential. It is a centralized electronic data storage which helps in decision making and strategic planning process of an organization. In an organization various tasks can be performed using data warehouses. So, it is good if an organization move beyond simple databases and opt for data warehouses.