The precursor to LIMS data analytics is structured data
Questions abound—about our health and the environment—for which laboratories are uniquely positioned to possess the answers. In fact, your laboratory’s biggest, most valuable asset may very well be its data.
Properly collated and analysed, data can lead to insight, knowledge, even power. But to find those answers and ultimately unlock the value of the data you hold, your laboratory will need strong data analytics capabilities.
In the span of only a couple of decades, IT strategies have evolved from data management for reporting to data warehousing for business intelligence (BI), and now to machine learning (ML) and artificial intelligence (AI) for massive data processing, pattern recognition, predictive analytics, and complex modeling. Even if your lab isn’t propagating petabytes of data into cloud storage for AI to comb, any data analytics effort, even simple analysis of operational data for internal process improvement, demands structured data that is reliable, accurate, and of high quality.
What is structured data?
Structured data is data that is captured and stored in organised ways, allowing it to be read, retrieved, and utilised for quantification, analysis, or extraction. Structured data formats and metadata can be easily read and retrieved by structured query language (SQL), for example, and then easily reported on or passed on for extract-transact-load (ETL) processes.
What isn’t structured data?
Data can also be unstructured or semi-structured, both of which are more difficult to search and organise and therefore are more problematic to analyse. Examples of unstructured and semi-structured data types can include images, audio files, emails, social media posts, data tables, and log files.
Even though unstructured and semi-structured data can be difficult to analyse in automated ways, it can still be useful in the laboratory setting for augmenting core test-and-result data for research purposes, for example.
Why is structured data important to data analytics?
Structured data is organized and readable, which makes it more accessible, sharable, and usable to data reporting and data analytics applications. The quickest, easiest analytics will be possible when your laboratory information management system (LIMS) creates and stores your laboratory data as structured data.
Knowing the importance of structured data to data analytics, the system architecture of your LIMS software can impact the success of your laboratory data analytics initiatives. If your laboratory management’s future IT strategy includes laboratory business analytics and data-driven insights for better laboratory decision-making and value creation, be sure to select a modern LIMS that is purpose-built to deliver structured data management.
Choose a LIMS that adds business value and insights
A modern LIMS like Clinisys Laboratory Solution™ automatically stores data inputs as structured data defined by metadata. Clinisys Laboratory Solution users, for example, can define unlimited Additional Information fields for endless possibilities and near-total flexibility in the data they choose to capture and structure into the laboratory software system. And because Clinisys Laboratory Solution stores these virtually limitless data fields as structured data, the system is uniquely positioned to return for reporting any and all data your lab chooses to input into it.
A modern, analytics-ready or AI-ready LIMS will:
- acquire data at the point of origin
- create metadata context around that data
- structure data in a reproducible way
- allow flexible and changeable data types
- protect data access to preserve data integrity
- search and output all data
Digitally transform your lab with Clinisys Laboratory Solution as your LIMS. With Clinisys Laboratory Solution, you will have your LIMS data at your fingertips for reporting, analysis, connectivity, test sharing, geographic growth, scientific collaboration, and more.
Related content
Why equipping scientists to harness digitalisation is key to driving laboratory innovation
Digital transformation can deliver significant benefits for laboratories and their customers, but success requires more than simply buying the latest technology.
How data-centric laboratory information systems create new value, using your laboratory’s own data – Clinisys
Data is an asset with value laboratories can’t afford to overlook. Read how your LIS or LIMS must put data at the center of your enterprise architecture.
Pitfalls and payoffs of moving your laboratory to the cloud
Consumers are embracing the cloud in their daily lives, and businesses are increasingly following suit. With more laboratories moving to the cloud, Imogen Fitt from Signify Research, outlines the opportunities and challenges that lie ahead.