Success Story

On-demand data generation at a large financial institution

Learn how a large financial institution moved from 5-day provisioning to self-service data with Curiosity’s Enterprise Test Data!

The problem

A centralized test data team took between 1 hour and 5 days to fulfil data requests, hunting for data in complex DB2 mainframe and a Google BigQuery warehouse.

The solution

Curiosity introduced automated, self-service data provisioning, with engineers and CI/CD tools running “find and makes” using self-service forms and APIs calls.

The benefits

Engineers and CI/CD tools enjoy instant, on demand access to the right test data, with repeating JSON generated into BigQuery and data found automatically in a DB2 mainframe.

The benefits at a glance

Data provisioning time reduced from between 1 and 5 days, to instant and self-service
Enterprise Test Data provides a common way of identifying and making test data.
Unlimited quantities and variety of data drive rigorous testing and development.
Enterprise Test Data automates test data searches through web forms and APIs.
Parallelization of tests and engineers shortens release cycles.
Complete test data coverage finds bugs early.

Manual testing vs delivery speed and quality

One of the world’s largest credit bureau’s faced lengthy test data provisioning bottlenecks, undermining both the speed and quality of their testing and development.

Vastly complex data

The sheer size and complexity of the data made manual data provisioning a significant bottleneck. When Curiosity started working with the credit bureau, data had to be found in a DB2 Mainframe, upon which a credit reporting system was built. Credit files were stored in a fixed file format, with intricate interrelations. The data provisioning team had to hunt for data to create files, validating it, and sending files back to test and development teams.

Lengthy waits for data

Before Curiosity began working with the credit bureau, there were never enough SMEs to find relevant data quickly enough. For simple data requests, an SME required 1-4 hours to find data, validate it, and send it in a file. Complex requests took 4-5 days, hindering development agility. This hindered data-intensive testing and development, further undermining software quality.

A modern approach to test data delivery

Today, Enterprise Test Data automatically hunts for the data needed to fulfil test case or user story definitions, automatically making data where relevant combinations cannot be found.

Accelerate Delivery Time - Curiosity Software

Self-service data “find and makes”

When no suitable data is found, Enterprise Test Data automatically generates the missing combinations on demand. This maintains the optimal data coverage needed for rigorous testing and development. It additionally feeds “gold copy” data for fulfilling future requests.

A reusable catalogue of data requests

Each query submitted to Enterprise Test Data becomes reusable and repeatable on demand. Stored user queries can be rerun automatically, providing on demand data that fulfils every past request, populating traditional instances, containers, virtual databases and more.

Synthetic data generation

Where no similar or matching data exists, Enterprise Test Data’s comprehensive data generation activity creates the requisite combinations from scratch. The rich data is generated directly to databases, or via message queues, files, and APIs.

Discover on-demand data generation

Read the full story to learn how self-service Enterprise Test Data can help you remove data provisioning bottlenecks!

On-demand test data generation

5-day provisioning reduced to self-service
Optimal quantities and variety of data on demand
Data ranging from DB2 mainframe to BigQuery

Read the full story

Manually finding and making data adds up to one of the most resource-intensive, time-consuming tasks in testing and development. Automating provisioning can make the difference when striving to hit release deadlines and stay on budget.

Senior Test Data Engineer

Read the full story

On-demand data generation at a large financial institution

The benefits at a glance