7 b] Explain Data Wrangling with a neat diagram.
Data wrangling is the process of transforming raw data into a suitable representation for various tasks. It is the discipline of augmenting, cleaning, filtering, standardizing, and enriching data in a way that allows it to be used in a downstream task, which in our case is data visualization.
Look at the following data wrangling process flow diagram to understand how accurate
and actionable data can be obtained for business analysts to work on. The following
steps explain the flow of the data wrangling process:
- First, the Employee Engagement data is in its raw form.
- Then, the data gets imported as a DataFrame and is later cleaned.
- The cleaned data is then transformed into graphs, from which findings can
be derived. - Finally, we analyze this data to communicate the final results.
For example, employee engagement can be measured based on raw data gathered from feedback surveys, employee tenure, exit interviews, one-on-one meetings, and so on. This data is cleaned and made into graphs based on parameters such as referrals, faith in leadership, and scope of promotions. The percentages, that is, information derived from the graphs, help us reach our result, which is to determine the measure of employee engagement:
