The Data Analytics Process: Explained

The data analytics process is broken down into 6 phases.

Ask, Prepare, Process, Analyse, Share, Act.

Ask = Define problems to be solved and establish stakeholder expectations. Figure out the KPI’s are and what you are trying to achieve from the data analysis process.

Prepare = Collect and store data for the upcoming analysis. Identify which type of data will be most useful, consider the time frame and which sources should be used.

Process = Find and eliminate any errors and inaccuracies from the data. Combine data sets and remove outliers. Check data to make sure it is complete and correct. This part is crucial as any mistakes here can result incorrect or inaccurate analysis.

Analyse = Use the relevant tools to transform the data to make conclusions.

Share = Interpret results and share with others to help stakeholders make decisions. Data visualisations are helpful in this stage to share your findings in an effective way.

Act = Use the insights generated to come up with actionable steps which can be implemented to reach the desired KPI’s set out in step 1.

The 6 phases of data analysis help you effectively conduct data analysis on a consistent basis.

Steps Prepare and Process are usually conducted by Data engineers.

Steps Analyse and Share are conducted by Data Analysts and Scientists.

The Act phase is usually assisted by Business Analysts so they can consider wider, Macro and Micro, sector specific information to create a useful plan of action.

The data analysis process is simple to follow, however each stage needs an expert to conduct it so the process yields useful results, which are free from bias, errors and inaccuracies.