Reconciliation
Verifying the consistency and integrity of data between source systems and target data stores through automated reconciliation processes.
Expertise
Data Solutions Test
Make data quality essential
Many organisations highlight a lack of trust in their data as a key concern. Proving data quality isn’t all about assuring that dashboards look great, it’s about having confidence in the data journey from source to reporting.
Data goes through many transformations before it’s ready for presentation. Data solutions testing confirms that rules, logic and processes work correctly at each step, helping your organisation avoid issues that impact reporting, operations and analytics.
What is Data Solutions Test?
While traditional software testing seeks to verify user interactions, functions and journey’s, data solutions testing encompasses the whole range of data management and processing. Automating these tests through an efficient framework such as PyTest puts organisations at a significant advantage when it comes to having confidence in their data and being able to demonstrate this to regulators, auditors and their customers.
Validation
Ensuring that data conforms to predefined rules, formats, and constraints to maintain data integrity and consistency.
Quality
Assessing the accuracy, completeness, consistency, timeliness and validity of data using quality metrics and profiling techniques.
Transformation
Validating the correctness and effectiveness of data transformation processes, including mapping, conversion, cleansing and enrichment.
Integration
Testing the seamless integration and interoperability of data across different systems, platforms and data sources to ensure data is accurate and complete.
Acceptance
Verifying that data outputs and reports meet business and regulatory requirements.
Why Structure Matters in Data Solutions Testing
Data moves through multiple transformations, so a structured testing approach ensures the business and technical rules behind those steps are built correctly. It means validating end‑to‑end behaviour, key scenarios, and performance, not just checking values in a table. Automating this through frameworks like PyTest improves consistency, reduces manual effort, and gives clear evidence of data quality for regulators, auditors and customers.
Our Data Solutions Test Approach
We combine automated and manual testing, applying automation wherever possible to increase coverage, speed up feedback and reduce errors.
Automated Data Validation
Automated frameworks like PyTest create scripts to validate data against predefined rules, constraints and thresholds, ensuring consistency and accuracy.
Regression Testing
Automated Regression tests are conducted to verify the impact of changes on existing data structures, transformations and integration processes.
Data Sampling
Sampling techniques are employed to analyse representative subsets of data for validation, profiling and quality assessment purposes.
Manual Data Inspection
Data analysts and subject matter experts perform manual inspections and exploratory data analysis to identify anomalies, outliers and data quality issues.
Our Data Solutions in Action
“The future of work is here. Though people are working in a hybrid manner, their desire for collaboration and offering exceptional workplace experiences is higher than ever. Our partnership with Seriös Group has enabled JLL to rise to this challenge through innovation in data and analytics.”
“Our partnership with Seriös Group has brought game-changing improvements to both our football performance and commercial operations. Through the power of integrated data, we're creating a smarter, more agile, and more engaged club.”
“By working with Seriös Group to establish best practices and implement Seriös ONE Launchpad, we’ve successfully transformed our data into a true strategic asset. With a unified and governed data platform, we can gain real-time insights, achieve a single view of our customers, and streamline our operations, allowing us to make smarter, faster decisions.”
“The flexible architecture of Seriös ONE Launchpad positions Equans for future growth, allowing the expansion of Condition Based Maintenance (CBM) to additional sites and integration of more data sources. The ongoing remote monitoring has meant quick identification and resolution of asset-related issues, extending the lifetime performance of the hospital's infrastructure while minimising carbon emissions.”
“Partnering with Seriös Group has proven to be a highly effective extension of our data capabilities. The flexibility and depth of expertise they offer has provided us with a reliable source of data support on tap, enabling us to scale and adapt quickly to evolving business needs.”
Data Solutions Built for Your Organisation
Your tech stack needs to be the right one for your organisation. Whether you use Azure, AWS or GCP, we build data platforms that fit your infrastructure and specialise in a core set of technologies proven to deliver results quickly.
Frequently Asked Questions
Got questions about Data Solutions Test? We’ve got answers...
What is Data Solutions Testing?
Data Solutions Testing ensures your pipelines, transformations, and outputs behave as expected so teams can trust the results. It validates data quality from source to presentation, checks key business rules and scenarios, and identifies issues early in the data journey. With automation frameworks like PyTest, organisations can test more consistently, reduce manual effort, and give regulators, auditors, and customers clear evidence of data accuracy.
Why does Data Solutions Testing matter?
Data passes through many stages before it is used. Data Solutions Testing confirms that rules, logic and processes work correctly at each step, helping you avoid issues that impact reporting, operations and analytics.
What does your Seriös Group testing approach include?
We use a mix of automated and manual testing to validate pipelines, business rules, transformations, and outputs, giving full coverage with fast feedback.
Why is Seriös Group’s approach to Data Solutions Testing different?
We build your testing approach into the delivery from the start, not added at the end. By validating rules, transformations and performance early in the data journey, you reduce rework and shorten delivery cycles. This gives your organisation faster, more consistent and outcomes‑focused data solutions that are easier to trust and scale.
How does Seriös Group deliver Data Solutions Testing?
Our data solutions experts apply a structured framework that aligns testing to your architecture and delivery approach, ensuring your data solutions perform consistently from ingestion to presentation.
How does automation support Data Solutions Testing?
Automated tests provide consistent coverage, run quickly and reduce manual effort. Using frameworks such as PyTest gives you repeatable checks that can run throughout delivery and provide clear evidence of data quality for regulators, auditors and customers.
