The implementation of robust processes for data organisation and management is a task often overlooked within engineering applications, but it can unlock productivity gains from several different sources:
Having a single data source allows groups to ensure they are working under the same assumptions, with databases allowing reliable multiple-user connections and data consistency control.
With history, logs and related data sets, you can trace the data you are using back to its source or ancillary datasets. Example: finding the physical test data associated with the reference simulation.
When your data is consistent and has logical storage, you can start automating some tasks that do not directly add value to your business. This can be data processing, running simulations, and even report writing.
Storing data in separate local instances can create inconsistencies within local datasets, leading to incorrect reporting or analysis. Implementing automation can also reduce the likelihood of user errors.
With structured data, you can start to plan your technology roadmap with the confidence that you have a solid base. Different business areas can analyse the same data by developing tools built off the database to their requirements. Organising your data is also the first step towards machine learning to take your business to the next level.
Robustly storing your data with consistent labelling enables the development of a wide range of data-driven activities to enhance your engineering processes. These activities range from statistical analysis of your project results, anomaly detection, and convergence checks to uncertainty quantification and AI-based methods.
Overall, structuring data in a database increases the efficiency of your business, with faster access, fewer errors and less wasted time. Sabe has worked with multiple companies to implement processes for data management to extract the benefits mentioned above.