Be sure your IoT data is fit for purpose with data quality
Ensure operational excellence in your data-driven processes. We specialise in validating IoT data, ensuring it meets stringent standards for optimised manufacturing and secure infrastructure operations.
Bad data quality causes flawed data-driven processes
Low-quality data can have a severe negative impact on data-driven processes such as manufacturing or monitoring and control of critical infrastructure. Poor quality data can lead to wrong decisions and undesired behaviour of control systems and AI-based data algorithms that can increase operational costs, affect downstream users, and cause lost revenue and reputational damage.
We can help you ensure that your IoT data is fit for purpose
High-quality and fit-for-purpose data is a prerequisite for all data-driven applications. Data quality significantly influences AI applications and machine learning algorithms, e.g. digital twins, for optimised and sustainable manufacturing processes and secure and efficient operations of critical infrastructure.
We can help ensure your IoT data meets stringent domain-specific standards and application-specific rules by developing and defining the data validation rule set for your application and helping implement the data validation process in your organisation. We will provide clean, analysed and visualised datasets, supporting informed decision-making while securing the integrity of your manufacturing or infrastructure data.
processes
Our process is based on:
- ISO 8000-61 – Data quality management: Process reference model
- Methodology for Data Validation from the European Commission
Both are based on the Plan-Do-Check-Act cycle from ISO 9001, which means our process is grounded in globally agreed processes for data quality management.
We also utilise the following material to strengthen our process:
- A certification as a Certified Data Management Professional (CDMP) provided by the Data Management Association (DAMA)
- "Fælles sprog for datakvalitet" by the Danish Agency for Digital Government (in Danish)
We also follow the development of international standards within IoT and ML as a member of Danish Standard and ISO/IEC JTC 1/SC 41.
"Open source was a completely new concept for us. It was amazing to see what it could do. The development time for creating process data logging from new machines has at least been cut in half with the new software – on an annual basis, that's 100 hours saved. And when it comes to licenses, we are talking about saving 25-30,000 DKK annually compared to the previous systems. So, there's quite a bit of money in it."
/ Henrik Hildebrandt, Mechanical Engineer
Trelleborg Sealing Solutions
Whitepaper: Value-driven IoT business model innovation
/Article
White paper: Data spaces in Denmark
/Article