Basic data analytics using Microsoft excel

Microsoft excel, is a powerful tool when it comes to data analysis. Data analytics is the process of collecting data, cleaning, processing and visualizing the data to provide insights or enable making of data-driven decisions.
We manipulate data using functions such as sorting and filtering, removing duplicates.
We can use different formulas and functions like sum, average, count, vlookup, and other functions to manipulate the data.
We use pivot tables to instantly summarize large data sets.

Organizing data.

Before we can analyse any data, we first need to clean and organize it, which ensures the data is uniform so functions and calculations give correct information.

in the baove image, we see that the data is in columns and rows that are uniform for each criterion. This makes it easier to do complex calculations such as averages, sums, and even create pivot tables as well as interactive dashboards from the data.

sorting and filtering.

To arrange data in a coherent, understandable manner, we use sort and filter.

1. On the ribbon, click home
2. Go to sort and filter, from here you can sort in ascending or descending order.

Data analysis

We use functions to analyse a data set. From there, we deduce patterns and trends. We understand what the large data set tells us.
These functions include the following,

1. Sum. This adds value to give the total of the specified range of figures.
2. Average. This gives the average of the numbers that are provided in the specified range.
3. Vlookup. This function helps us look for a value and match it to another value.
4. Logical if, and/or help us create complex filtering criteria.
5. A pivot table is one of the most powerful features in Excel, as it automatically summarizes large data sets and groups them by categories. It calculates totals, averages, counts, and other key metrics instantly. Below is an example.

It allows us to view a summarized analysis of a very large data set in one or more Excel sheets.

Presenting data for decision making.

After the analysis, we need to present the results in an interactive way that allows users of the information to make informed decisions. We create such interactive dashboards using slicers.
To create slicers, go to Pivot Table Analyze and click Slicers as shown below:

The final presentation.

We now create an interactive dashboard that summarizes the most important metrics driving decision-making. Below is an example of an interactive dashboard:

WE have now done an informative data analysis project in Excel, from cleaning information, sorting, and analyzing to presenting information that enables clear decision making.