How Excel is Used in Real-World Data Analysis.

Microsoft Excel is a widely known spreadsheet software primarily used for organising, analysing, and visualising data. Several people have interacted with Excel in various ways and at different levels. Personally, I use Excel primarily for data entry and have always considered myself to be well-versed in the software—until last week, which left me quite literally questioning my proficiency.

It has only been a week of learning Excel at LuxDevHQ, and I have already experienced its power in data cleaning and preparation, data analysis and exploration, data visualisation, collaboration, and reporting.

Real-world data is always messy and unstructured; thus, it first needs to be cleaned, and Excel has an array of tools to do this efficiently. Built-in tools can be used to remove duplicates, while features such as 'Format Cells' are useful for standardising formats, especially in scenarios where we have inconsistent data types, such as numbers stored as text or improperly formatted dates. Through data validation, Excel restricts input to predefined formats or values, for instance, dates within a range, or creating a dropdown list of data that can be entered in specific cells, preventing errors during data entry and ensuring data quality from the start.

In terms of analysis, Excel can be used in different sectors, for instance, by HR professionals to monitor workforce trends like employee performance and turnover, which can be easily visualised and relied upon when making data-driven decisions on issues such as hiring.

Sales and marketing teams can also leverage Excel through the use of features such as Pivot Tables and Charts, which allow them to group customers in terms of demographics and purchase history. This is vital for gaining insights into campaign effectiveness and sales performance. This data can be used to adjust strategies to improve future engagement and revenue.

There's quite a lot that can be achieved with Excel, and as I continue on this learning journey, one thing that has changed my perspective on data is the importance of cleaning your data, as this is the basis of any accurate form of analysis.