Big Data & Analytics Testing

According to an analyst from Gartner, "The average organization loses $8.2 million annually through poor Data Quality."

Big data is in the large volumes of data – both structured and unstructured, but it’s not the amount of data that’s important. It’s what organizations do with the data that matters. These huge volumes of data provide an opportunity for businesses to make smart decisions by using appropriate analytics.


Testing Big Data : 3 Big challenges

1. we need to verify more data and do it faster

2. we need to automate the testing effort

3. we need to be able to test across different platforms


This is where three Vs of big data came from –

1. Data Volume: Huge amount of data flows through systems and is to be tested and validated for its quality

2. Data Velocity: This is the speed at which new data is getting generated, in general when the velocity with which data can be analyzed is greater then profitability is more for an organization

3. Data Variety: Big data comprises large data sets – draws from the text, images, audio, video; which may be structured, semi-structured or unstructured.

Big Data & Analytics offerings

QuaiTlabs offers the following Testing services in Big Data and Analytics

  • Data Ingestion Testing: Structured, unstructured, and semi-structured data sources
  • Testing Migration to Big Data Lakes: Structured to NoSQL data sources
  • Analytics Testing: Predictive models
  • Visualization Testing: Data Insights
  • Data Quality in Big Data: Acquire, cleanse, and integrate data
  • Performance and Security Testing

Following are the stages of the testing involved in the BigData Testing –

Understanding Customer problem

Understand the customer problem – Who is the customer, preferences, problem statement, preferences, etc.

Gathering required Data & Analyzing It.

Solving a big data problem requires gathering an enormous amount of data; once you have access to such data, analysis of volumes of data is necessary to understand and enrich the customer experience.

Testing Data

Testing analytics applications requires exploration of the Social Media, Mobility, Analytics, and Cloud (SMAC) world.

The three key data characteristics include Volumes, Velocity, and Variety; data characteristics to be tested and testing to be done include.

Data Volumes
Data Variety
Data Velocity

Testing the BI/BA Applications

Analytics solutions should be tested for standard testing techniques such as Functional and Usability Testing, Security Testing, Performance Testing, Usability Testing –

  • Functional and Usability Testing – To check if the application provides the correct information, e.g., providing a single view of the customer from multiple data sources.
  •  Security Testing – to focus on authorization and authentication of users and availability of data.
  •  Performance Testing – To focus on data accuracy and performance under high load.

There are not many testing tools around BigData – the testers at QualiTlabs are experts in using BigData Design and Development tools and able to test BigData. In some cases, we use Tools such as query surge can help test up to 100% data quickly.

Try Our Services

We offer No Cost Pilot