The field of Big Data is growing at a rapid pace. Businesses are realizing the value from daily social media input as well as from wireless sensor networks to gauge the daily changes in personal activity, trends, science, weather, traffic – all sorts of information that can help businesses grow to meet the demands of change in social, business and global arenas. These Big-Data sets are noted by the size, the speed, and variation referred to in most instances as the 3-Vs: volume, velocity and variety.

  • According to IBM, by the year 2016, 90 percent of the world’s data had been created within that past 12 months. Now, it is growing so fast that it would be the equivalent of a company the size of Google being created every day.
  • A Global Data Quality Research report commissioned by Experian Data Quality, (produced by Dynamic Markets) states that 99 percent of organizations have a data- quality strategy in place.

Big Data Quality and Testing Trends

In testing Big Data, there are certain parameters that must be met to get quality results. Some of these are validating process, making sure the data is complete, it is accurate, and having automation of regression testing to make sure that the programs you are using are utilizing the updates and other new changes correctly.

Developing a Big-Data Implementation Plan

There are so many companies offering testing for Big Data that it is hard to know if you’re getting the quality that you need and deserve. Companies should not only have a reliable track record of the companies they have successfully serviced, but they should also have a professional team in place that is trained in the following:

  • Have a solid knowledge in the background of Big Data and how the 3-V’s relate.
  • Have a solid background in specific query languages (SQL) such as the top three: MapReduce, Pig-Latin, and Impala
  •  Since all SQLs work on top of Hadoop® MapReduce Program and its distributed file system, a solid knowledge of how these languages interact in the categories of Procedural – Map-reduce in Java, Declarative in HiveQL by Apache Hive™ and Apache Impala™ and Scripting in Apache Pig™ Latin and Apache Spark™ is needed.
  • Additional skills in knowledge of architecture and analytics is necessary.

Why BrickRed Systems?

BrickRed Systems’ professionals know their stuff when it comes to Big Data testing.  We have solutions to meet your needs and can offer a comprehensive package of tools, processes and skilled resources as well as the reassurance you’ll have working with professionals who have a solid reputation and a global presence.

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