Essentiality of Data Wrangling

In a nutshell, Data wrangling is the process of cleaning, structuring and enriching raw data into a desired format for better decision making in less time. To roll out a new software product commercially irrespective of any domain in the market,  360-degree quality check with test data is mandatory.  We can correlate this with a visualized concept of a new vehicle.  After completion of vehicle manufacturing, fuel has to be injected to the engine to make it operational. Once the vehicle starts moving,  all the quality check, testing get started like brake performance, mileage,  comfort etc with thousands of other factors which are decided/concluded during design phase. Similarly, we should have data to verify and evaluate all the expected functional behaviour,  consolidated during the design phase of the software product.

Without data (considering here as a test data i.e. the data for test purpose only), we can’t  perform any functional like performance behaviour of the product. To assemble and consolidate test data, we have to adopt manual or automated process to convert or map data from one raw format to another format so that converted format of data can be flown across all the component in the developed product and eventually quality control/testing team can initiate their activities to certify the software product.  This process where data format conversion takes place from one format to another is called data wrangling. Like how crude oil is refined to desired fuel which is mandatory to run or test a newly manufactured vehicle.

Written by
Gautam Goswami

Can be reached for real-time POC development and hands-on technical training at gautambangalore@gmail.com. Besides, to design, develop just as help in any Hadoop/Big Data handling related task. Gautam is a advisor and furthermore an Educator as well. Before that, he filled in as Sr. Technical Architect in different technologies and business space across numerous nations.
He is energetic about sharing information through blogs, preparing workshops on different Big Data related innovations, systems and related technologies.