The six data analysis phases
Six data analysis phases will help you make seamless decisions: ask, prepare, process, analyze, share, and act. Remember that these differ from the data life cycle, which describes the changes data undergoes over its lifetime. Let's walk through the steps to see how they can help you solve problems on the job.
Step 1: Ask
Solving a problem is possible if you know what it is. These are some things to consider:
Questions to ask yourself in this step:
Step 2: Prepare
You'll be able to decide what data you need to collect to answer your questions and how to organize it to be functional. You might use your business task to determine the following:
Questions to ask yourself in this step:
Step 3: Process
Clean data is the best; you must clean up your data to eliminate possible errors, inaccuracies, or inconsistencies. This might mean:
Questions to ask yourself in this step:
Recommended by LinkedIn
Step 4: Analyze
You will want to think analytically about your data. At this stage, you might sort and format your data to make it easier to:
Questions to ask yourself in this step:
Step 5: Share
Everyone shares their results differently, so summarize them with clear and enticing visuals of your analysis using data via tools like graphs or dashboards. This is your chance to show the stakeholders how you solved their problems and got there. Sharing will undoubtedly help your team:
Questions to ask yourself in this step:
Step 6: Act
Now it's time to act on your data. You will take everything you have learned from your data analysis and put it to use. This could mean providing your stakeholders with recommendations based on your findings so they can make data-driven decisions.
Questions to ask yourself in this step:
These six steps can help you break the data analysis process into smaller, manageable parts called structured thinking. This process involves four primary activities: