How I Structure My Data Analytics Reports (Google Slides & PowerPoint)

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As a Data Analyst, you will have to compile reports to present your analysis to the executive team or whichever team you are working with.

You might get a list of deliverables to present in your report and sometimes you will have to go with a general format.

After completing the Data Analytics Professional Certification course on Coursera, I had the chance to add case studies to my portfolio, and at the end of each, I was to compile a report with a list of deliverables.

After compiling reports for a while, I came up with a 6-point general report format. You can use either Google Slides, PowerPoint, or any presentation application you use.

1. Introduction
2. Data Sources
3. Documentation of cleaning and manipulation
4. Summary of Data Analysis
5. Key Visualizations and Findings
6. Recommendations

Introduction

Here, you want to summarize the background of your analysis, talk about the company or project you are working on, and why you are going ahead with the project.

You will also include your business task and problem in this introduction. Here is a sample of mine.

Business Task: Analyze personal Twitter data to find trends in tweet patterns and how personal Twitter account is used.

Problem Statement: How can trends identified from tweet patterns be utilized in future tweets to earn revenue from Twitter Blue?

Data Sources

In this section, you will describe all the datasets you are using. Use the following format:

1. Describe where the datasets were downloaded from.
2. Link the sites for the datasets if possible.
3. Indicate if the data is from a public or a private license and if it is trusted.
4. Describe the datasets, the columns, and what each dataset summarizes if there are more than one.

Documentation of cleaning and manipulation

Make sure you note down any cleaning you do on your datasets and the tools you employed for your analysis. You can use a Word document to note down the changes you made or you can make comments in the tool you are using for your analysis to make sure you don’t forget.

Also note down the manipulation, if you changed the data type of a column or you created a new column for calculation note them down.

Summary of Data Analysis

This section involves explaining the steps you used in your analysis, what metrics did you look out for? What functions did you use? Which columns did you analyze in the data? Note them all down.

Key Visualizations and Findings

Make sure to list the key findings from your analysis that you did in the step earlier, list them out in layman's terms, and remember that the people you are presenting to will not be data analysts so make it as plain as day.

Recommendations

Here, you will provide high-level recommendations from the key findings, make sure they align with the goal and business task you were given, and also answer the problem statement of the project.

Note: You don’t have to bombard the report with all the information. You can make bullet points and explain them as you present them. That way it makes it easy for the audience to follow.

If you have a time frame, make sure to practice and make sure you stay within the timeframe when you present.

You can find the report I compiled for the BellaBeat Case Study below.

BellaBeat Case Study by Adedoyin Ademola.

You can find my portfolio below:

Adedoyin Ademola's Portfolio - Case Studies & Projects

Check out my Kaggle here.