• In software testing companies, the number of domain-based applications (HealthCare, IT, Manufacturing, Banking, Academia etc.) are tested where data keep on growing exponentially day by day which induces the need of Big data testing too.
    In such applications, along with the testing of features of software product, the verification of processing of the data (also called Database testing) plays equally important role.

    Big Data testing is based on the concept of 5 V’s:
    - Volume: The amount of data.
    - Velocity: The speed of coming data.
    - Variety: Type of data.
    - Veracity: Trustworthiness of data.
    - Value: Importance of data.

    The testing of big data deals with different types of data format:
    - Structured Data [ERP, CRM]
    - Unstructured Data [Video, Audio, Image, Doc.]
    - Semi Structural Data [CSV, XML, JSON]

    In General, Database testing can be carried out with below steps for web application testing services:
    1. Data Staging Validation: The data taken from various sources(e.g. weblogs, RDBMS etc) and the data which is pushed to database frameworks (e.g. Hadoop, Talend) is validated here.

    2. Process Validation: This phase is related to validate the accuracy of result obtained after processing from the processes like Map Reduce. Business logic is tested at every node in it. The values of Key pair are generated and tested.

    3. Output Validation: It store the data in the Data Warehouse and make sure that data is accurately represented in target UI.

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