Increasing Business Value with Effective Test Data Management

While digitalization is driving the business world today, technologies like Mobile First and IoT have gained momentum and enterprises are getting influenced to enter the world of mobility, thereby opening endless opportunities.

The flow of data and information is limitless with the surge in adoption of digital trends and technology advancement. Effectively using and managing information is critical to streamlining operations, attracting & retaining customers, and pursuing new business opportunities.

However, these needs increase demands on underlying IT infrastructure and database systems that are often not up to the task and create an array of workload challenges.

The Role of Test Data Management

As enterprises look to deliver high-quality applications at the lowest possible cost, they need to build out a more agile application infrastructure, and that includes a robust and comprehensive test data management strategy.

According to a report published on Markets and Markets, “The test data management market is expected to grow from USD 584.6 Million in 2017 to USD 1,060.9 Million by 2022, at a Compound Annual Growth Rate (CAGR) of 12.7%.”

The factors driving the test data management include increased quality of test conditions and growing need for leveraging data integration tools, optimized storage and processing costs, better technical support to black-box testing teams.

The increased adoption of test data management solutions and services by several industry verticals, such as, IT, Telecom, BFSI, healthcare and life sciences, government, and retail have boosted the need for test data management.

Test Data Management plays a key role in ensuring quality roll out of applications at the right time. As a service/practice, it has matured in most organizations. The predominant activities include sub-setting, masking, data refresh and synthetic creation standardized through Test Data Management, Extract Transform Load (ETL) or Database (DB) tools.

In the prevalent agile environment, it is imperative to strategize the test data management efforts.

Test Data Management practices in an Agile environment that improve business value

While there are frequent sprints in an agile methodology, the need for an appropriate test data is high and managing this test data yields better results.

The best practices to be followed for handling test data management in an agile environment include –

• Identifying the appropriate data to test – The data that needs to be tested should be identified appropriately. To do so, one needs to have an end-to-end exposure to the overall business process.

• Creating a replica of Production data – As the data in the production environment is the best candidate for usage, it is advisable to create a replica of it. This will result in having realistic databases that will act as a baseline for all the test data repositories in the management framework.
• Keeping the data safe and secure – In the process of simulating the real data, it is also important to keep the simulated data safe and secure. This will help create a secure repository in the test data management framework and can be reused without any malicious attacks.
• Refreshing the data after every regression cycle – Keeping the data in sync with the latest built features is important in creating an effective test data management solution. This helps maximize your test efficiency.
• Automate as many test cases as possible – It is always recommended to automate as many test cases as possible, paving way for agility and less prone to errors.

By proper implementation of test data management solutions, it becomes very promising for enterprises to increase their business value while assuring customer experience.

However, in the era of digitalization and ever-changing customer needs, every methodology is prone to challenges. It is imperative for businesses to stay focused and take steps to overcome any challenges that come their way.

Overcome Information Architecture Challenges and Identify New Business Opportunities

Enterprise architects and CIOs can modernize their data management practices to overcome information architecture challenges and identify new business opportunities. The key pointers include the following:

1. Solutions powered by Artificial Intelligence (AI) and Machine Learning (ML) that directly optimize the performance of data management, which then has a ripple effect throughout a business.
2. Rapid reporting and analytics, ranging from computing and processing to compression and data skipping.
3. As IT budgets continue to plateau, it is imperative for enterprises to use staff and financial resources efficiently.
4. Flexibility in choosing the right cloud infrastructure. Depending on your unique needs, consider which deployments best meet your requirements: on-premise, private cloud, hosted cloud, public cloud, or a hybrid model that leverages various platforms.
5. Increased scalability and constant availability through shared storage clustering, supplementing on-premise and private cloud with public cloud, and scaling cloud storage and independent compute.
6. Support for new data types and sources such as audio–visual content, event data, social media data, physical documents data, IoT sensor data, and Email Content.
7. Open source technology integration by leveraging community innovation and avoiding vendor lock-in and gain access to more data. Enterprises must ensure that open source solutions are secure, well-integrated, and properly governed.

According to a recent study conducted by Forrester, “88% say they need to perform analytics in near-real time on stored streamed data.”

To Sum Up

While test data management tools have matured over a period, there are still many areas where processes are not standardized. Hence, businesses are not able to yield efficient results that a robust test data management function can deliver.

Implementing standardized test data management solutions can significantly improve quality, reduce risk, and decrease cost for businesses.

Cigniti’s extensive Test Data Management services help you improve test effectiveness by using accurate test data, institutionalizing test data management process, implementing test data creation & simulation, data masking, data quality management, data archiving, automating test data management systems, & protecting data sensitivity.

The key services offered by Cigniti Data Governance practice include Data profiling & analysis, Data governance, Data provisioning, Data generation, Data environment management, and Data privacy.

Cigniti has partnered with vendors such as Neotys, SmartBear, enov8, HP, TestPlant, AppDynamics, Tricentis, and more having expertise in various test data management tools which give our clients the option to choose the right tool based on their requirement and budget.

Get in touch to let us help you transform and increase business value with effective test data management techniques.