Validata Blog: Talk AI-powered Testing

ConnectIQ Use Cases

ConnectIQ Use Cases

Generate and secure all the data required for rigorous testing and provision it on demand to distributed teams!

Challenges

To deliver quality software on time means ensuring that the right data is provisioned to the right environments at the right time. This is often the last thing to be addressed, and most times not effectively.

With most banks and financial services organisations undergoing a digital transformation, there will be more and more IT development and testing activities and the use of real production data is the fast lane to acquire data for such purposes.

Traditional approaches would proceed with making full-production copies of test data—upward of tens of millions of records—to use in the testing and development cycle. And the process is often repeated for each layer of testing. After each change in the production environment, all the other environments need to refreshed and this process of provisioning and masking the production data could take days or even weeks.

The use of production data for testing only provides as much as 20% functional coverage, focusing testing only on the ‘happy paths’.

Testers usually spend up to 50% of their time looking for data, and as much as 30% of their time trying to resolve data-related defects. This leads to testing bottlenecks which make true agility and Continuous Delivery impossible.

The absence of proper test data is a major reason why nearly two thirds of business applications reach production without being properly tested.

The opportunity

Validata ConnectIQ is an intelligent DataOps platform - faster, more scalable and more privacy-conscious, which accelerates data delivery, maintains data security and compliance. It enables teams to quickly and directly manage their data for a variety of use cases from DataOps, analytics, test data and environments provisioning, to customer experience transformation and cloud migrations.

ConnectIQ generates and secures all the data needed for rigorous testing and provisions it to distributed teams on demand! It combines data masking, data virtualization and synthetic data generation into a single, powerful centralised platform, that delivers masked virtual or synthetic data within data centers and across private and public clouds.

Synthetically generated or virtual data enables broader test coverage and negative testing. It lets you simulate data types and ranges and includes outliers, boundary conditions and erroneous data that almost certainly will not appear in your production data.

Use Cases

Here are a few use cases where ConnectIQ platform can be used to achieve the biggest impact:

Cloud Migrations
While most companies are in favour of cloud adoption for their data and software development, they also face the risk of exposing their customer data, which slows down their move to the cloud or they are poised to use “hybrid” solutions that are limiting the benefits. ConnectIQ is the ideal solution to address these issues and accelerate cloud adoption.
Companies Using Offshore Development & Testing
Data security has become a stumbling block for companies to remain competitive. We are able to secure your data without breaking your existing applications, enabling our clients to accelerate their data security program implementation and keep costs at a manageable level.
Accelerate Agile & DevOps adoption
ConnectIQ is ideal for providing the DataOps expertise that is required to successfully implement DevOps. Organisations can no longer be depending on a DBA who is running around for everything.
Companies in regulated industries
Banks and financial services organisations that need to be in compliance with data protection regulations such as GDPR, CCPA, etc, and need to maintain the highest levels of data security and privacy.
Unlock Digital Transformations
With digital transformation being at the center of any business activity, companies need to release new applications at the speed and quality required to remain competitive. QA and Dev teams need to have access to quality data on demand and eliminate data bottlenecks and lengthy provisioning times.

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