Testing Services

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Delivering 100% Accuracy Through Testing Services

IDS's QA and software testing services aim to ensure that software fully meets its requirements and user expectations. 

This involves a wide range of requirements, but will typically include:

  • One-time testing
  • Functional testing
  • Compatibility testing
  • Localization testing
  • Performance & load testing
  • Usability testing
  • Security testing

IDS are able to provide a wide range of testing services, and have proven expertise across a range of sectors,  including but not limited to highly complex or regulated sectors such as higher education,  public sector,  healthcare and financial services.

As leaders in data certainty,  IDS prioritize accuracy in everything we do - and that applies also to our software testing services. Whether in a production or pre-production environment, we focus on delivering 100% accuracy, 100% of the time. 

Because we have a dedicated testing team in house, as well as access to the full suite of iData tooling, we can generate synthetic or obfuscated data to add rigor to our testing services, 

 

ETL Testing with iData

ETL — Extract/Transform/Load — is a process that extracts data from source systems, transforms the information into a consistent data type, then loads the data into a single depository. ETL testing refers to the process of validating, verifying, and qualifying data while preventing duplicate records and data loss.

ETL testing ensures that the transfer of data from various and diverse sources to the central data warehouse occurs with strict adherence to transformation rules and is in compliance with all validity checks. It differs from data reconciliation used in database testing in that ETL testing is applied to data warehouse systems and used to obtain relevant information for analytics and business intelligence.

 

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The Future of Continuous Testing revealed by IDS CTO & Co-Founder, James Briers

The Future of Software Testing

In 2022, the software industry will see more adoption of codeless automated testing tools. The fact that reviewing test cases will become easier makes people want to adopt them more. Software testers are also looking for ways to increase effectiveness and save resources with codeless automated testing.

At IDS , we are able to augment human testing with a suite of machine-learning tools to deliver 100% accuracy and detailed reporting, in any testing framework, while at the same time, saving clients time and money.

Continuous Testing as The New Norm

Now that agile practices have matured and DevOps initiatives have entered the corporate agenda, continuous integration (CI), continuous delivery (CD) and continuous testing (CT) have emerged as key catalysts for enabling quality at speed.

Continuous testing is - by far - the most difficult. Even with automated solutions in place, testing and data quality practices can fall behind in a fast-paced program. 

Continuous testing, executed correctly, serves as the agile process' centerpiece. It brings together everything to automate business intelligence, focus teams on accurate information and align business requirements with technical goals. 

This is, therefore, essential to control risk and protect data quality when reporting or dashboarding results in an ever-complex and fast-paced world of modern application delivery. 

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No Nonsense Test Data Strategy

At IDS we use a simple yet efficient approach to managing test data which is delivery framework agnostic,

it does not matter if you are in an agile world or a traditional delivery approach. Every journey starts with a single step and in this case, we recommend establishing a high-level strategy that captures the main components of a test data management strategy.

This strategy can evolve over the duration of your journey to delivering your test data capability. The reason for this approach is to ensure that your approach is mobile and have an ability to maneuver. By creating your own data, you have an opportunity to increase the testing coverage and reduce business risk. This process is complex to master and will require input from subject matter experts within the organization who can help provide deeper insight and understanding.

We focus on four main components at a high-level

  1. The purpose of your data
  2. Data set type selection
  3. Test data management approach
  4. Business intelligence for environments.

The Purpose of Your Test Data

How will your data be used? How you will use the data will drive how you create and maintain the data. We have several uses for test data, and it is not always for testing purposes, we have experienced a multitude of differing reasons to own and manage test or non-production data effectively. Each use has its own requirements.

Below are a number of key examples;

Training Application: To help support the training of business users on the application they will require access to production-like data to make the training exercises more realistic and meaningful. This use of test data will be on a lower consumption than the more development and test functions.

Development: Developers use test data too! Some unit tests will require data to ensure the functionality being developed is delivering as promised. As with training, this would generally be a lower consumption of data and would be less destructive in its usage.

Test Automation: This is the golden ticket in terms of the beneficiaries of owning a test data management strategy. To deliver efficient test automation, you must have a mechanism for managing test data which supports frequent execution of your tests. Either generation of test data or refreshing your data back to a base state prior to execution. Having a sophisticated approach to test data management will empower your automated testing solution to shift to the next level and support Continuous Testing,

Continuous Deployment and DevOps Models: Without consideration of test data in this area, you will fail to deliver any of those models. With performance testing, the volume of data is key! Being able to consume huge volumes of data in the right state must be part of the solution. 

 

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Protecting Sensitive Data Through Software Testing

IDS' Focus to Face the Challenges of Continuous Testing

Our focus is to repeatedly deliver quality engineering with intelligent automation, digital business assurance and fully automated dashboards to provide a single version of the truth for all programs and projects.

IDS accelerates automated quality engineering for enterprise application testing on SAP, Salesforce, ServiceNow, Oracle, and many other popular enterprise applications so that organizations can innovate faster while reducing business risk.

By sustaining a concentrated testing focus on the real-time status of the data's quality, a major financial organization's cost of taxonomy assurance was reduced by 90% and enjoyed general project savings of 70%. 

It is through this rigor and end-to-end testing that IDS delivers 100% data certainty, through 100% of the journey, 100% of the time.