Using Big Data and Analytics Testing, retail industries across the globe are trying to uncover insights about their customers, business models, products, and operations. Read more: https://www.cigniti.com/blog/big-data-in-retail/

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Harness the power of Big Data in Retail

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Harness the power of Big Data in Retail
Retailers are vying furiously to expand their share of the customer's wallet in a market plagued by poor economic growth and
expensive costs.
Retailers are seeking to increase efficiencies and cut costs while operating within narrow single-digit percentage margins.
Big Data in Retail
Retailers are finding that traditional database management technologies can't handle the power of Big Data.
The retail business demands solutions that may assist them in gaining access to this customer and product data, understanding,
and playing with customer behavior trends, and ensuring their continued relevance and survival in a highly competitive market.
While consumers expect customization, they anticipate a seamless experience across online and offline platforms. They'll go to
a different retailer if they can't quickly make a purchase.
Retail merchants wanting to boost sales and customer happiness can use retail analytics and merchandising analytics to solve
these issues.

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Harness the power of Big Data in Retail
Why is it important to have a good strategy for Big Data Automation Testing
A big data testing strategy is necessary in a number of areas in Big Data. Database testing, infrastructure and performance
testing, and functional testing are all sorts of testing used in Big Data initiatives.
QA testers can utilize big data automation testing technologies to ensure that output data is properly loaded into the
warehouse by comparing output data to warehouse data.
Big Data Testing challenges
It's normal to have difficulties while testing unstructured data, especially if you're new to using tools in large data scenarios.
Here are some of the challenges encountered while testing Big Data applications –
• Many companies currently store exabytes of data in order to run their operations. This massive amount of data must be
audited by testers to ensure its accuracy and usefulness to the business. Even with hundreds of QA testers, manual testing
of this volume of data is difficult.
• A considerable rise in workload volume can have a major influence on the big data application's database accessibility,
processing, and networking. Despite the fact that big data applications are built to handle massive amounts of data, they
may not be able to handle massive workload demands.

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Harness the power of Big Data in Retail
Cigniti’s end-to-end testing methodology addresses overall Big Data & Analytics Testing requirements, including test data
needs, metrics definition, and tooling.
Our Big Data & Analytics Test Automation solutions help organizations pick the best model for their business needs and
generate test reports on the efficiency and effectiveness of predictive analytical models.
The offerings from Cigniti Big Data Testing Practice include Requirements Ambiguity Testing, Data Quality and ETL Testing,
DW Dashboards/Reports Testing, System and Integration Testing, Performance and Stress Testing, and BI Application
Usability Testing. Our value-adds are Custom Test-lets for Consumer Partitioning & Social Indexing, and Test and Process
Templates.
Consult our experienced team of experts to overcome your challenges related to big data testing, data migration testing,
data analytics testing, and big data performance testing, and harness the power of Big Data in the Retail Industry.
Read Full Blog at:
https://www.cigniti.com/blog/big-data-in-retail

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