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Big Data Testing- Challenges, Benefits and Best Practices

Big data is a collection of large datasets that cannot be processed using traditional computing techniques. Performance & functional testing are the keys when it comes to Big data testing. It is very different from traditional data testing in terms of data, infrastructure & validation tools. To know all about big data testing, check out this presentation.

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Big Data Testing- Challenges, Benefits and Best Practices

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  1. BIG DATA TESTING VERIFY STRUCTURED AND UNSTRUCTURED DATA SETS BUGRAPTORS

  2. Big Data Testing It involves checking various characteristics like conformity, accuracy, duplication, consistency, validity, data completeness, etc.

  3. Testing Parameters • DATA STORAGE • COMMIT LOGS • CONCURRENCY • CACHING • TIMEOUTS • JVM PARAMETERS • MESSAGE QUEUE

  4. Why Big Data Testing Big data deals with the data that are large and complex, difficult to process and does not fit well into tables. If Big Data systems not tested appropriately, then it can affect business.

  5. Big Data Testing Stages OUTPUT VALIDATION PHASE DATA STAGING VALIDATION MAP REDUCE VALIDATION

  6. DATA ACCURACY Overall Benefits QUALITY COST IMPROVED BUSINESS DECISIONS MINIMIZES LOSSES AND INCREASES REVENUES IMPROVED MARKET TARGETING AND STRATEGIZING

  7. Tools For Bigdata Testing • Hadoop • HPCC • Storm • Qubole • Cassandra • CouchDB

  8. Challenges in Big Data Testing LARGE DATASET AUTOMATION VIRTUALIZATION Automated tools are not equipped to handle unexpected problems that arise during testing Virtual machine latency creates timing problems in real time big data testing. Need to verify more data and need to do it faster

  9. Best Practices TESTING BASED ON REQUIREMENTS SAVE TIME PRIORITIZE THE FIXING OF BUGS CLEAR TEST OBJECTIVE COMMUNICATION

  10. HOW BIG DATA TESTING WILL BENEFIT YOUR ENTERPRISE?

  11. Real-time Data Validation There are need of some filtering, sorting and analysis to ensure that the captured data is valid and useful.

  12. Reduced Downtime Deployment of Big Data applications revolving around predictive analytics. It helps to improve data quality and related processes of the application which further reduces the overall downtime.

  13. Less Threat to Data Quality Rigorous testing of data can save data from becoming degradable and redundant.

  14. Does Your Big Data Require Testing? Checkout our offerings for Bigdata Testing Services

  15. PHONE MAILING ADDRESS 240-241-6894 5858 Horton Street, Suite 101, Emeryville, California, USA EMAIL info@bugraptors.com Let's work together WWW.BUGRAPTORS.COM

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