How Big Data analytics works:

  • Stage 1 – Business case evaluation – The Big Data analytics lifecycle begins with a business case, which defines the reason and goal behind the analysis.
  • Stage 2 – Identification of data – Here, a broad variety of data sources are identified.
  • Stage 3 – Data filtering – All of the identified data from the previous stage is filtered here to remove corrupt data.
  • Stage 4 – Data extraction – Data that is not compatible with the tool is extracted and then transformed into a compatible form.
  • Stage 5 – Data aggregation – In this stage, data with the same fields across different datasets are integrated.
  • Stage 6 – Data analysis – Data is evaluated using analytical and statistical tools to discover useful information.
  • Stage 7 – Visualization of data – With tools like Tableau, Power BI, and QlikView, Big Data analysts can produce graphic visualizations of the analysis.
  • Stage 8 – Final analysis result – This is the last step of the Big Data analytics lifecycle, where the final results of the analysis are made available to business stakeholders who will take action.