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ganeshmoorthydu
Advisor
Advisor
0 Kudos

Many times, creating a customer like mass data is a big challenge because of dependencies of data with one another, longer duration it takes for creation. Below table shows different methods been followed and challenges associated with it

Process

Challenges

Copying Customer Data and scramble it

Though  the data is very accurate , it is extremely sensitive, May demand for NDAs or approvals etc from different stakeholders,  - hence this could be a time consuming process

Replication of data base rows through scripts

It is extremely complex to create right combination of data.  Even smaller mistakes will lead to creation of junk data in mass.

Create data through report and iterate it for mass creation

Extensive support from development team is needed. If there is wide variety of data needed, the It may hurt the development team's bandwidth

Often the quality of data is compromised due to its complexities .There is a much easier and reliable method for mass data creation which is data creation through Load testing tools.

Creating data like customer is the cleanest way of creating customer like data. Load testing tools (Eg. Loadrunner) provides us the facility to simulate concurrent users (Customer like users) which is the fastest way to start and create data. Record a script the basic flow of data creation, identify different parameters, and feed with right data if needed, Optimize the script & run the script for any number of iterations. Another unique advantage of this method is, this runs faster than any functional tool. Mostly any scenario can be scripted in 1 day and can be run with adequate users to create data.

STC Performance team follows this method of mass data creation for volume testing  and able to create clean data in quick span of time. Eg. 1Million BPs with different relationships, attributes etc in 1 day.