How to use Excel in Real world Data Analysis

Can you imagine the world without Microsoft excel? Picture doing all your calculations manually, sifting through huge datasets by hand, and trying to make sense of it all—with a high risk of errors and inconsistencies. It would be absolute chaos.

Thanks to Microsoft corp. we get to have Excel that helps us key in data, clean the data, analyze and visualize it to make informed decisions. Microsoft Excel is a powerful, free and easy-to-use tool accessible to all. It is used across all sectors from healthcare to quality control to education to business to environmental sustainability etc.

Excel plays a critical role in transforming raw data into meaningful insights. It helps identify trends, predict future outcomes, and track performance across various metrics.

From my experience working in an analytical lab, Excel has become an everyday tool when it comes to:

1. Analysis of different chemical parameters
2. Monitoring turn-around time of samples in the lab
3. Tracking performance of quality control samples over time
4. Evaluating analysts’ performance based on their KPIs etc.

One of my best features on Excel is the Pivot Tables and Pivot Charts. Creating pivot tables to filter and sort out specific and important metrices helps in identifying trends and patterns that can be hard to point in raw data. For a business, it is crucial to identify top products/services, clients, monitor sales during different seasons e.g winter and summer, how discount rates affect the sale of products and so on. With pivot tables in place, pivot charts are used to visualize using either bar graph, line graph, pie chart or a combo of two different charts.

Excel has a rich library with formulas and functions that a lot of insightful data can be extracted from key indicators within a data set. From the basic arithmetic formulas SUM, AVERAGE, DIVIDE to complex logical functions using IF, AND, OR to conditional formatting and LOOKUP functions has made data analysis even more powerful.

Working with Excel at a deeper level has helped me develop a stronger sense of responsibility. The data I process—whether it’s cleaned, transformed, or analyzed—is often used to make critical decisions at the departmental, inter-departmental, or organizational level. That’s why accuracy, attention to detail, and integrity are non-negotiable when it comes to Excel-based data work.