Important challenges to successfully implement Big Data Testing

 

Important challenges to successfully implement Big Data Testing

Testing has become end-to-end, cross-functional operation, collaboratively involving all teams throughout the product lifecycle. Application testing is an ever-changing domain, driven by technological advancements, changes in business processes and the growing sophistication of system and applications. In the article below you will find the big data testing challenges you should know about. But before going into more details let us show you why testing is required and why it is considered one of the prominent part of a successful software application.

  • To ensure that the resulting product match with the user requirements and its demanding customer use.
  • Due to the use of a number of the operating system, browsers and devices it is necessary to test it on each device separately.
  • Something that works when one person is using it may not work when hundreds of people are using it.
  • There’s always a chance that a user really will do that no matter how silly it seems.

 

  1. Huge Volume and Heterogeneity

One of the biggest challenges with big testing is the huge data itself. Prior businesses stores their data in gigantic but nowadays data will be store as petabyte and even Exabyte data. The overall data is extracted from various offline and online resources, in order to achieve the daily basis tasks.  For checking the quality of such huge data of whether it is fit for business or not, testing can be performed at each end of the business infrastructure.  Due to huge data size, it is not possible to test the whole data.

  1. It is Difficult to Understanding the Data

Understand a big data is difficult as compared to small data. Same is the case with huge data testing, tester study the data each day but they are not able to get all the point at once as huge business data may change on daily basis or on weekly basis. Understanding the data is a big challenge for experience tester in term of data volume, velocity, variety and its value to the business.  Without knowing in detail the nature of any huge data it is impossible to write effective test cases, strategies and improvement suggestion in the application.

  1. Lack of Technical Expertise and Coordination

With the fast-growing technology, the trends of the testing algorithm are also changing. It is necessary for the tester to understand the big data challenges with respect to the fast-growing and technological world.  One of the mistakes every tester has to be is that they are thinking that they are working under the beyond of regular algorithm of manual testing and automation testing, but on the other hand big data challenges increases and the test cases fail to understand as a result.

The content mention in the above article will help you to know more about the big data testing challenges for all type of application whether it is a web application, software application, mobile application or desktop application.

Remember, don’t exhaust your customers! Test, Test, Test and Test some more!