the 4 stages of data analytics (pace)

The 4 critical stages of data analytics (PACE)

There are 4 stages in data analytics and it can summarize by using the word PACE. Each of these 4 stages is critical and will help you analyze your business problems using a data-driven approach. Read on to understand each of the 4 stages.

Prepare your data

In each level of data analytics, you will need to clean your data. Cleaning data refers to extraction of details, convert dates to readable format, combining data, any other actions that make your suitable for analysis. If your data is not cleaned, the analysis you perform will not be of good quality, no matter how much time you spend analysing your data. That’s why people say Garbage In Garbage Out (GIGO). In each level, the way to prepare the data is different. Hence, this milestone is needed for every level of data analytics.

Analyze your prepared data

With the data cleaned and prepared, we can go into data analysis. Analysing the data right will give you maximum return from your analysis and data. There are different approaches and tools we could use to analyze data and. In this milestone, we need to stay focus on Analysing using different data analytics approaches.

Communicate your analysis

Don’t keep the insights to yourself. Show off your insights to your peers and boss. Communicating your insights effectively is as important as your analysis. Using the PACE framework, you will be able to learn the rules and tools on creating an effective report or dashboard for your analysis and wow your audience.

Evaluate your goals

When you have successfully completed the PAC, it is time to evaluate your goal and see if it is still valid. If it is, you can continue with the entire process. But if meeting your initial goal means having to set up a new one, this is the time to do so.

Business functions that are likely to use of data analytics




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