Data Warehousing
Background
A Database Management System (DBMS) stores data in the form of tables, uses ER model and the goal is ACID properties. For example, a DBMS of college has tables for students, faculty, etc.
A Data Warehouse is separate from DBMS, it stores a huge amount of data, which is typically collected from multiple heterogeneous sources like files, DBMS, etc. The goal is to produce statistical results that may help in decision makings. For example, a college might want to see quick different results, like how the placement of CS students has improved over the last 10 years, in terms of salaries, counts, etc.
Need for Data Warehouse
An ordinary Database can store MBs to GBs of data and that too for a specific purpose. For storing data of TB size, the storage shifted to Data Warehouse. Besides this, a transactional database doesn’t offer itself to analytics. To effectively perform analytics, an organization keeps a central Data Warehouse to closely study its business by organizing, understanding, and using its historic data for taking strategic decisions and analyzing trends.
Benefits of Data Warehouse:
- Better business analytics: Data warehouse plays an important role in every business to store and analysis of all the past data and records of the company. which can further increase the understanding or analysis of data to the company.
- Faster Queries: Data warehouse is designed to handle large queries that’s why it runs queries faster than the database.
- Improved data Quality: In the data warehouse the data you gathered from different sources is being stored and analyzed it does not interfere with or add data by itself so your quality of data is maintained and if you get any issue regarding data quality then the data warehouse team will solve this.
- Historical Insight: The warehouse stores all your historical data which contains details about the business so that one can analyze it at any time and extract insights from it
Data Warehouse vs DBMS
Example Applications of Data Warehousing
Data Warehousing can be applied anywhere where we have a huge amount of data and we want to see statistical results that help in decision making.
- Social Media Websites: The social networking websites like Facebook, Twitter, Linkedin, etc. are based on analyzing large data sets. These sites gather data related to members, groups, locations, etc., and store it in a single central repository. Being a large amount of data, Data Warehouse is needed for implementing the same.
- Banking: Most of the banks these days use warehouses to see the spending patterns of account/cardholders. They use this to provide them with special offers, deals, etc.
- Government: Government uses a data warehouse to store and analyze tax payments which are used to detect tax thefts.
There can be many more applications in different sectors like E-Commerce, telecommunications, Transportation Services, Marketing and Distribution, Healthcare, and Retail.
Reference :
http://www3.cs.stonybrook.edu/~cse634/presentations/DataWarehousing-part-1.pdf
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