Image Source: Unsplash
For a long time, data management has not only been necessary for a successful laboratory, but it is also a crucial difference between success and failure.
In the digital economy of 2023, organisations can get access to more data than ever, all of which aids in the understanding and improving of processes – ultimately helping to reduce wasted time and finances.
Without efficient data management, an organisation puts itself at risk of falling behind the competition, with slower operations, poorly informed decisions, and a higher chance of cyberattacks and identity theft.
For laboratories creating materials to supply to the market, however, data management has a number of factors. Different types of data management include data preparation, pipelines, governance, security, modelling, ETLs, and more.
This makes it difficult for labs that need all of their data in one place, with the ability to actually conduct a comprehensive analysis. It’s also the reason why many labs are turning to materials informatics.
What Is Materials Informatics?
Materials informatics (or MI0) has been around since 2011, but it’s only in the last few years that its application has been spreading – just as digitisation has made a vast amount of data to become more accessible.
To give it a broad definition, materials informatics is the use of data and ML (machine learning) to give insight into business, processing and scientific fields. It does this by learning from past experiences to optimise tasks, input parameters and predict output properties.
What Is The Connection Between Materials Informatics And Data Management?
In 2023, the Application of Materials Informatics in Industry data management has proven crucial. Because it is made up of various technologies from various fields – including properties, experiments, cloud computing, and security – materials informatics has the ability to handle vast amounts of data at high speed, which similarly helps to increase the flow of innovation and accelerate the traditional steps to define processes.
When it comes to data management, one of the most urgent challenges for organisations comes in the lack of organisational memory and knowledge. The same is undoubtedly true in the field of science. Because data is spread across several areas, it has become difficult to gather it together and analyse it, which means that not all the data is actually being recorded.
With materials informatics, however, all data can be gathered together on one platform, increasing the access and visibility of all knowledge. This then provides a real solution for extracting the insights of that data, using a combination of AI and ML to analyse, visualise, and then apply insights and predictability.
The Value Of Materials Informatics
Whether it’s for processing, materials development, or simple data management, materials informatics allows organisations to efficiently leverage their data and utilise advanced AI algorithms to uncover every hidden insight.
Not only this but the ML elements of materials informatics grow to understand the specifics of an organisation over time, meaning it continues to optimise the way it uncovers and analyses the data to further develop operations.
With the field of materials informatics advancing at a rapid pace, it is likely that more and more laboratories will take advantage over the coming years.
