To strip a data analyst’s job to its very core, it involves taking data and turning it into insights a business can act on to make more profit. What does that process actually look like step by step?
I recently worked on a project that required the exact steps I’m about to take you through. The goal of the project was to streamline a monthly 22-market marketing performance report process, making it quicker and less prone to human error. The process once required four people to put in a month’s worth of time to complete, and throughout a LOT of unnecessarily busy work. I cut that process down to just one person, some technology, and a week’s time to pull together.
So here were the steps involved in streamlining the process. I’ve also included in parentheses the tool(s) I used for each step.
- If your data comes from multiple sources in various formats, you will want to create a data collection template that will allow you to easily combine the data every month. Excel is still the most universal tool for storing data so I recommend using Excel to create the template. If you are looking at more than a few hundred thousand rows of data, however, you may want to consider building a database.
- Ideally, when you give someone a template, they follow it. But we’re human, and humans mess up. That’s when you want to leverage a tool like Alteryx to further validate and clean the data, then join together all data sets so you only have one or a few files to work with.
- You’ve spent hours gathering and cleaning the data, and now you finally arrive at the most interesting part: visualizing the information for others to quickly spot trends and make decisions on how to act on them.
- Outline trends you see right away and work with the marketing execution team to further understand what the most important takeaways are. At this point you will have taken some numbers and made them into money drivers. That’s it, you’ve done your job!
- Continue evolving the data cleaning and blending process to save more time and energy every time you repeat the cycle; allow the process to be malleable to data structure changes and anomalies
- Ask for feedback from the marketing execution and other relevant teams and act upon them
- Don’t underestimate the importance of data visualizations in enhancing your story