Big Data and Analytics Testing

Big Data and Analytics Testing

Decipher your data and untangle insights that can

keep you one step ahead of your competition

Know More

Decipher your data and untangle insights that can

keep you one step ahead of your competition

Know More

With the advancement in technology on the rise, enterprises collect and consume a substantial amount of data and are rapidly adopting Big Data programs to manage this crucial data. As a result, organizations face numerous challenges in end-to-end testing in the best possible test environments, and a robust data testing strategy is what they need the most.

Big Data Testing Challenges

Lack of data and Heterogeneity

These days, businesses store gigantic amounts of data extracted from different online and offline sources to carry out their day-to-day business activities. Testers are expected to examine such massive data to make sure they fit the purpose.

Emotion Check

Data that is generally obtained from sources like tweets, social media posts and text documents act as primary data feeds for unstructured data. And keeping the emotions in check is one of the biggest challenge when it comes to unstructured data.

Understanding Data

The continuous validation and monitoring of the 4Vs of Data –Variety, Volume, Value and Velocity, is classed as effective testing strategy. But the real question lies in identifying the data and its effect on the business. Therefore, testers need to comprehend business rules and the association between various divisions of data, along with its connection between multiple data sets and how it benefits the business users.

Lack of Technical Expertise and Coordination

For enterprises, it is essential to ensure coordination between the testing, developing, and marketing team to understand data mining from different sources, data sorting, and before and after processing of algorithms. In addition, businesses ought to invest in training programs for Big Data to build the test automation solutions.

Stretched Deadlines & Costs

If the testing process is unstandardized and weak for re-use and optimization, the test cycle will cause increased costs, delivery slippages and maintenance issues. Hence, they need to be fast-tracked to implement proper infrastructure, validation tools, and data processing practices.

Big Data Service Catalogue

FUNCTIONAL TESTING

NON-FUNCTIONAL TESTING

Big Data Sources Extraction Testing

Performance Testing

Data Migration Testing

Security Testing

Big Data Ecosystem Testing

Data Analytics & Visualizations Testing

Cogniwize Testing Capability

Effective Knowledge
Management to Upskill

Cogniwize’s training frameworks enable faster upscale. In addition, users find its Big Data lab and its Knowledge Management portals helpful since it gives them the ability to train well and produce (PoC) proof of concepts for detailed client interactions.

Validate Data
Touch Points

Framework for Big Data testing on Hadoop architecture, where we compare the source data by pushing it into the Hadoop system to ensure they match.

Our framework supports to:

Pre-Hadoop process validation

Hadoop Map Reduce process validation

ETL process validation

Analytical reports validation

Tools and Accelerators
to Improve Productivity

In-house utilities/ Customizable MapReduce and Pig Latin scripting templates increase productivity by 10%. Allows data migration testing between the EDWs and Big Data store and supports automatic data quality testing of Big Data stores.

Big Data Automation Testing

Cogniwize’s Automation Testing solution validates unstructured and structured data sets, plans, tactics, and fundamental practices within different sources in your application.
It provides:

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Improved Business
Decisons

Genuine data acts as a positive feature for the user. Our comprehensive data quality analysis techniques ensure you get the right kind of quality data to analyze all sorts of risks, thus helping users to make informed decisions.

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Minimizes Losses and
Increases Revenues

Precisely analyzed data results in minimal losses. Our custom-made Map Reduce automation scripting and & Pig Latin automation scripting templates examine filter conditions a lot quicker than any other templates in the market. This isolates the various data types to improve customer relationship management, increase effort savings, and reduce time-to-market by 20%

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Uninterrupted
Integration

We perform a thorough study of the most recent and fresh data requirements and integrate suitable data migration, acquisition, and integration testing strategies to ensure it is a smooth process. This has helped businesses reduce time to market by 15% by creating better strategy and enhancing market goals.

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Quality
Cost

It is imperative to test the data beforehand, so it does not affect the functioning of the organization. Enterprises leverage our top-of-the-line in-house data conversion, discrepancy and reporting services to enhance testing productivity by up to 30%, thus reducing the total cost of quality.

Better decision making for improved market targeting and strategizing with Big Data and Analytics testing

Talk to our well-trained and highly experienced Big Data Expert to know more

Contact Us

Better decision making for improved market targeting and strategizing with Big Data and Analytics testing

Talk to our well-trained and highly experienced Big Data Expert to know more

Contact Us