Harness the power of 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

Cignitis 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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