Basic Data Analytics Using Microsoft Excel

Basic Data Analytics Using Microsoft Excel

Microsoft Excel is a powerful tool for data analytics. Data analytics involves collecting, cleaning, processing, and visualizing data to extract insights and support informed, data-driven decision-making.

Excel provides a variety of built-in tools and functions that allow us to manipulate data—such as sorting, filtering, removing duplicates, and using formulas to compute key metrics. With features like PivotTables and slicers, users can quickly summarize large datasets and build interactive dashboards.

Organizing & Cleaning Data
Before any analysis can take place, data must be cleaned and organized. Proper organization ensures that values are consistent and structured, allowing functions, formulas, and PivotTables to produce accurate results.

Typically, well-formatted datasets are arranged in rows and columns, with each column representing a unique field (such as Date, Product, or Price). When data follows this structure, calculating averages, sums, and other metrics becomes much easier, and advanced features like dashboards become possible.
Sorting and Filtering Data
Sorting and filtering help present data in a more meaningful and easy-to-understand way.
Sorting allows you to arrange data in ascending or descending order.
Filtering lets you display only records that match certain criteria.
To apply these tools:
Go to the Home tab on the ribbon.

Click Sort & Filter.
Choose your sort order or filtering criteria.
These functions give us the ability to focus on specific segments of a dataset and identify patterns quickly. Data Analysis Using Excel Functions

Excel provides numerous formulas and functions that help analyse data and extract insights. Some commonly used ones include:

SUM – calculates the total of a selected range of numbers.

AVERAGE – returns the mean value of a dataset.

COUNT – counts how many cells contain numbers in a range.

VLOOKUP – searches for a value and returns corresponding data from another column.

Logical functions (IF, AND, OR) – help create complex filtering or conditional rules within datasets.

Using these functions, we can uncover trends, compare values, and understand what the data is telling us. PivotTables: Summarizing Large Datasets
PivotTables are one of Excel’s most powerful analysis features. They allow users to:
Automatically summarize large datasets
Group records by different categories
Calculate totals, averages, and counts instantly
Create multi-dimensional data views
PivotTables make it possible to generate reports and insights quickly without manually writing formulas for each calculation.

Creating Dashboard
By combining PivotTables, charts, and slicers, we can build an interactive dashboard that highlights key metrics and supports better decision-making. Dashboards give stakeholders a simplified, high-level view of important trends and patterns within a dataset.

Conclusion
Using Microsoft Excel, we can move through the full data analytics workflow from cleaning and organizing data, applying analytical functions, summarizing results with PivotTables, and finally presenting insights through interactive dashboards. This end-to-end process transforms raw information into clear, actionable knowledge that drives decision-making.