Data Analytics Lifecycle

Have you ever wondered how researchers analyse the data they gather? Here are the steps involved in this process!

The researcher starts with the discovery stage where they gather relevant data, whether by analysing the market, reviewing studies in this field, or using other methods appropriate to the nature of the project. Once the task is completed, the researcher prepares the collected data so it becomes homogeneous and usable. This data prep then leads to model planning, which means identifying methods and techniques that will help establish a relationship between the relevant variables selected for the study, enabling model building. The researcher also determines and optimizes the workflow to be carried out.

Once the model has been built, it has to be tested with the prepared data. The results will help determine the strength of the model and any changes needed (hardware, algorithm settings, adjusting variables, etc.). The refined model can provide results that may be used for prediction, classification or other purposes, depending on the case studied. These findings are then shared with stakeholders in the research project. This is the result communication phase.

The last step is to operationalize. The research team submits a report, a source code and a technical document before launching the pilot project that will implement the model in a production environment.