emmanuel-uduma / sales-performance-analysis

Here is a simple analysis on excel, I intended to draw inferences on the company's sales for a month.

Sales-Performance-Analysis

Ever wanted to try out your skills as a Data Analyst newbie? Having learnt so much on Excel, R programming, SQL, Python, and even visualization tools like Power BI, Tableau etc. Jumping into a mega project is an awesome thing to do, but getting starting even with the basics is the best and can inspire someone, as well as guide your audience through your growth process.

As a Data Analyst newbie (by Data Scientist Network, PH Community), I have decided to work on an excel project building a dashboard on a days' sales data for a supermarket in the month of January.

The questions to solve with this analysis includes: · Given a sales target of 300 quantities of goods sold, what size of products met this target? · What categories of products has the highest quantity sold? · What size and category of products had the highest sales price?

To do this, the raw data for the sales on that particular day will be needed, as well as the visualization of the information drawn from the sales data.

I guess this doesn't look like too much work, does it?

Take a deep breath and lets get started……

DATA COLLECTION:

Getting a structured data of the supermarket wasn’t difficult cause I had the privilege of downloading the excel format, which made my work a lot easier.

DATA CLEANING AND PREPARATION:

After getting the Excel data set ready, I had to format and clean the data set by removing duplicates and to make sure there are no empty cells and stuffs that will lead to a biased analysis. Also to enable filtering the data set.

The following steps where done is cleaning the file: • Borders were put on the document. • Font style was changed to suit the taste of the Analyst. • The column "Accessment" was created to indicate the product size that met the days' target of 300 quantities.

DATA ANALYSIS AND VISUALIZATIONS:

The data set was analyzed using Excel pivot table and pivot chart. Below is the dashboard that gives a visualization of what happened to their sales on that particular day.

Results:

• The different sizes met their target of 300 product quantities sold.
  • The poultry category has the highest quantity of products sold 4566.
  • The large sized snacks category has the highest sales price.
  • The dashboard also showed that the medium sized products had no failure to achieving the target of 300 quantities sold.
  • Although the poultry products has more quantities sold, the large sized snacks products generated more revenue to the sales department for that day.

FINALLY, THIS IS A WRAP!

Does it look difficult to do? I guess not.

Furthermore, I decided to play around with Power BI, since I am still exploring the visualization tool. And here is what I came up with.

Thank you for reading, till I come again next time.

Kindly drop any feedback and recommendations. I will be grateful to contributions.

I am open to networks and collaborating with you as an individual or a company, to work on any data analytics and visualization project.

Cheers to Growth!