Big Data & Analytics Testing

It trends such as big data analytics, cloud, mobility and virtualization will continue to grow, although these are considered as fairly expensive technologies to develop, test and maintain.

Big Data – these two words are heard widely in every IT organization and across different industry verticals. The concept of big data refers to a huge amount of data, petabytes of data and huge mountains of data. With ongoing technology changes, data forms an important input for making meaningful decisions.


Three Vs of big data –

  1. Volume: Huge amount of data flows through systems and is to be tested and validated for its quality
  2. Velocity: This is the speed at which new data is getting generated, in genaral when the velocity with which data can be analyzed is greater then profitability is more for an organization
  3. Variety: Big data comprises large data sets – draws from text, images, audio, video; which may be structured, semi-structured or unstructured.

Big Data Analytics application test considerations

The test strategy should include the following testing considerations in ordeer to test the application properly –

  • Data Extraction Testing
  • Data Quality Analysis
  • Reports and Visualization Testing

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