Data Used

Data: Call Centre Data with over 30,000 rows from 1 October 2020 to 31 October 2020

Data Cleaning & Analysis: Microsoft Excel

Visualization: Microsoft Excel

Phase 1: Format and Clean Data

Step One

When working on an Excel Data Set, I begin by duplicating the Original Data Sheet into a “Working Sheet”. This serves as a failsafe should there be an issue during my analysis

• After duplicating the Sheet, I expanded all the columns (ALT + H + O + I) and distinguished the header rows from the rest of the data with Bolding and Colours
• I froze the Header Row so I was aware of the data I was looking at when scrolling through the document and added a “S/N” column to act as the first column. This easily provide a total count (32,941 records)

Step Two

Next, I looked at the datatypes in my dataset. There are 13 columns in this dataset

• Most of the Data Types (10) are text, however were 3 meant to have different categorisations
• Cast_Score and Call Duration in minutes was changed from “General” to “Number” using the Number Format under the Home Ribbon
• Call_timestamp had records that were Dates and others that were Text. As the Data Types were mixed, the Number Format could not be used to change them. So I used a feature called “Text to Column” under the Data Ribbon. This process successfully converted all the records to dates, given the same format (MDY) was used