An Integration Testing on Average Categorized ECommerce Based Data to Improve Their Performance Using Automation Tool
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2017, Vol 5, Issue 6
Abstract
in today’s rapid increasing digital world many numbers of electronic commerce companies have making transaction per second which makes it more sensitive data transaction process which need very much care. Big data is a growing trend in ecommerce and online marketing. Big data enables businesses to gather insights about their customers through monitoring their purchasing habits and decisions. By using big data, businesses can focus more on customization and personalization for their customers’ shopping experience. This can be done by tracking customer browsing patterns and monitoring loyalty programs. In this thesis we are going to focus on those customers who make transaction for particular data. On the basis of this analysis we will categories the whole data transaction in this manner where all the transaction are divided into three parts and at the end of the day all three category have got average data transaction. On that resultant average data we perform unit testing after that we integrate all the data into single form and apply integration testing and provide necessary suggestion to improve performance.
Authors and Affiliations
Kumar Shankara Bhargav, Sunil Sharma
Keywords
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