Big Data Testing: The Key Components and the Advantages
Big Data has moved ahead of the buzzword and is now becoming mainstream business technology at a rapid rate. Big Data and Analytics are being adopted by companies at skyrocketing rates and everyone right from the small businesses to large multi-national corporations are innovating and implementing Big Data strategies for enhancing their operations and leveraging the technology to provide value to their customers.
While the Big Data technology is still in its infancy and it will take a lot of time for the technology to mature to its true potential, companies have nevertheless begun building applications on the platform and are striving to use the technology for various applications including- providing customer-centric experiences by mapping customer behavior, offering personalized recommendations, predicting trends in businesses and industries to get prepared ahead of the time, etc.
With the rise in Big Data Application Development, there is a huge demand for Big Data testing services today. Since the field is relatively new, developers and testers find it challenging to learn the nuances of testing for Big Data applications.
Here are the key components of Big Data testing that are essential for any developer's or tester's consideration:
Validating the data includes checking the accuracy of the data, checking any replication issues, validating the data ranges for different data types so that each value in the database falls under an allowable range, cross-validation of data to make sure that the data is consistent with other aspects such as the relevance time-frame and the length of data, structured validation that ensures when multiple data values are combined under a single structure, the structure remains valid too!
- Data Staging Validation: Big Data comes in a variety of formats. It can be tabulated in the form of tables, semi-structured in the form of tags and categories, or unstructured in the form of videos and comments. As each kind of data is dumped into a data lake initially, before any analytics or operations are applied to the data, it is important to perform validations on the data.
- MapReduce Validation: In this step, the Big Data is processed using a MapReduce operation to obtain the desired results. The necessary business logic is tested first on a standalone unit and then on a set of units. The MapReduce operations are valid, and the resulting key-value pairs are checked for their accuracy. Then, the consolidation of data as part of the reduce operation is tested. And, finally, the output file is measured for parameters like the format of the file, the results in the file, etc., to make sure the file was generated according to the requirements.
- Results Validation: As the final step of the process, the output of the operations is validated for their accuracy and formats. The output data files are generated and are instantly moved to an Enterprise Data Warehouse. Here, the transformation rules are checked for whether or not they were correctly applied, the integrity of the resulting data is assessed, and the output information is compared against the HDFS system data to ensure there was no data corruption.
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This is the comprehensive series of steps followed to accomplish Big Data testing. When implemented carefully and with expertise, here are the benefits Big Data testing provides:
- Enhanced decision making as the data is properly validated and tested sound decisions can be made to excel an enterprise.
- The accuracy of the data can be assured as a result of thorough Big Data testing. With the right data, businesses will be able to figure out their pain points and will be in a better position to improve and establish themselves as a brand.
- Market goals can be met easily when a business has the right data at its disposal. Big Data enables companies to plan out predictive marketing.
- The profits of companies who leverage Big Data boost up since the insights the data provide them about the market and their customers enable them to deliver value and helps them excel as their business.
With a perfectly chalked out Big Data testing strategy, success is only a step away!