Big Data Testing

Big Data has gone beyond the imagination of just being a buzzword. Today, the concept of big data is widely accepted across companies irrespective of their sizes. However, still, there are companies who are struggling with the huge information that are involved in the business. According to a recent survey, Big Data Technology has seen 40% acceptance in the last year and this figure is going to increase in the coming years.

With the advancement of technology, Big Data has a bright future in the coming time; however, it is equally important to consider the challenges that might come it’s way as it grows. Though there are different ways to handle the challenges, there are still much to be done in terms of quality, as it requires skill and knowledge of data science.

The Importance of Big Data Testing

According to Gartner “Big Data is high-volume, high-velocity and/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation.”

There is no particular parameter to define the volume of big data technology. With the huge volume of data coming in from different directions, data gets quite dynamic in nature with the processing rate getting much higher. In fact, data could come from clouds and in different forms. Even the most reliable solution for data management finds it quite difficult to handle the tremendous volume of data.

Big Data Testing: Key Components

The processing of a huge amount of big data can be split into three basic components.

  • Data Validation: It is one of the most important components. Data Validation ensures that that is not corrupt. Here, the data source is checked and mapped with the exact business requirement.
  • Process Validation: The data is pushed to the right location after the data and source are matched. This process verifies the business logic node by node and against different nodes.
  • Output Validation: Data once generated is fetched in the data repository where it goes for further processing. Here, it is ensured that data is not compromised.
Big Data Testing: Benefits

Big data testing ensures that the data is accurate and has been validated. Moreover, it helps in the following:

  • Better Decision Making
  • Data Accuracy
  • Better Strategy
  • Increased ROI

You may also like: The Need for IoT Testing

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