Data Analysis in Five Steps

Data analysis is becoming an essential skill today, with so many streams of data to consider in our technical world. From the fitness tracker you might wear on your wrist to the click-throughs you make every day online, data is everywhere. But what actually happens when somebody analyses it? Here’s a simple breakdown of the five key steps in the data analysis process.

Ask the right question

Always begin with a clear and focused question. This could be anything from “Why are sales down this quarter?” to “Which marketing channel brings in the most loyal customers?” Your question will set the direction for the entire process, so take time to get it right from the start – after all, a well-defined problem is already half solved.

Gather your data

Next, you’ll need to collect the data to help you answer your question. This could mean digging deep into spreadsheets, approaching a data analysis company, or pulling reports from your social media or customer databases. Your data for analysis could come from internal systems or external sources like government records, public data or online APIs.

Clean your data

Your raw data is likely to need cleaning up before you’ll be able to analyse it, so take the time to do a little spring cleaning. You’ll need to check for missing values, remove duplicates, correct errors and make sure your formatting is consistent throughout all of your data. A data analysis company, such as //shepper.com, can assist with this.

Analyse the data

Now it’s time to analyse your data! You’ll dig into your data to spot patterns, trends and insights. You could use charts, statistical models, AI software or other software such as Excel, Python or Tableau. Your goal should be to explore the data from lots of different angles and start answering the original question you defined in stage one.

Tell the story

Finally, you can tell a story by interpreting your findings and sharing them. A report, dashboard or visuals that’ll help others interpret your data will help you to share your findings clearly.

Nina Brown