Data Warehousing (10 Blogs) Become a Certified Professional
24 Sep 2014

Introduction To Data Warehousing

What is a Data Warehouse?

A Data Warehouse is a central location where consolidated data from multiple locations are stored. Data Warehouse is not loaded every time when a new data is generated but the end-user can assess it whenever he needs some information. There are certain timelines determined by the business as to when Data Warehouse needs to be loaded whether on a daily, monthly or once in a quarter basis.

Going by the simple term, a ware house is a place where things are stored. It is the data that one procures from the transaction system. There are two concepts – Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP). The former is used to record the transactions and the latter is for analyzing.

Why is a Data Warehouse Required?

For a company to flourish, good decisions have to be the first base. For good decisions, all the relevant data has to be taken into consideration and the best source for that is a well-designed data warehouse. The concept of data warehousing is very simple: A central location or storage for data that supports a company’s analysis, reporting and other BI tools. The reason why its importance has been highlighted is due to the following reasons:

  • A data warehouse delivers enhanced Business Intelligence
  • It saves time
  • It enhances data quality and consistency
  • It provides historical intelligence
  • It generates a high ROI

What is ETL?

ETL means to Extract, Transform and Load. There are multi-disparate sources that are loading a data into the data warehouse. Hence, data needs to be extracted from different sources.  There is no consistency in the OTP system so the data that is coming in to the data warehouse has to be standardized. Usually, in the banking sector, they use mainframe systems which is a complex function but now it has been transferred to the data warehouse system.

ETL-EdurekaData Warehouse Architecture

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Creating and Populating the Tables

Introduction To Data Warehousing

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