Data Cleansing and ETL

Summary: Data warehouse plays a crucial role in defining the process flow in an organization. When you are designing a data warehouse, it is essential to make it go through cleansing and ETL. There are various reasons behind it. Read the article to know more.

A data warehouse is a system that produces data, scrubs it up, organizes the data and places it in the right order for data analysis, browsing and decision-making. We can say that a data warehouse helps different departments within an organization to work in a smooth way. There are many important elements of any data warehouse development process and data cleansing is one of them.

Data cleansing or data scrubbing is the process to stop undecipherable data from entering the data warehouse. During this process, all the records are checked for consistency & accuracy and some of them are even deleted or corrected. This is absolutely essential for data warehousing.

The process of data cleansing can occur within a single set of records or in multiple data sets. It is most of the times an intensive and contentious process that makes a data warehouse more secure.

What is ETL?

Extract, transform and load is a category of tools that will help in ensuring that the data is clean and confirms to quality standard before it is being entered into the data warehouse. The ETL tools supplied by the vendor are more easy to use for managing the data cleansing process on an ongoing basis. The tools are used for reading the incoming data and if they come across a data for which they have been programmed to transform, they will make changes in it before loading it into the warehouse.

You can use the ETL tools for extracting data from remote databases manually or through automatically scheduled events. Although there are other alternatives to purchase ETL but all this depends on the complexity and the budget of the project.

If you are working on smaller projects, the database administrations can write scripts that will perform the ETL functionality. Even Microsoft has a SQL server with a free ETL tool called Data Transforming Service. The tool is good but has a few limitations when it comes to ongoing administration of data cleansing.

Planning for Data Cleansing

It is essential for a data warehouse designer to map out the data before entering it into the data warehouse as soon as possible. Many aspects will change as the project will get mature but this documentation will serve as a valuable source to get commitment from data owners that they will not change the format of the warehouse without informing the designer.

Your very first step should be to create a list of data that will be extracted, transformed and loaded. One should also make a separate list of data that has chances of changing formats. The next step should be to decide if you want to purchase ETL tools or work with free tools..

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