Tech Brief: Smarter Data with Synopses & Correlation Tools
The challenge of working with large and complex data is not just about volume. It is about knowing what is meaningful, what is redundant, and what can be trusted to support decisions. In its latest tech briefs, the STELAR project introduces two tools that help make this process more efficient and intelligent.
These brief overviews offer a closer look at scalable methods for analysing patterns in data and summarising it effectively. Keep reading to find out how multivariate correlations are made practical, why approximations are not shortcuts, and where this research is already making an impact.
Eindhoven University of Technology: Smarter Ways to Handle Complex Data
Both briefs come from the Eindhoven University of Technology (TU/e), a partner in STELAR with a strong focus on data systems and AI. TU/e researchers contribute to the project by developing methods that improve how data is interpreted and managed – particularly when precision, speed, and scale must go hand in hand.
This research does not stay in the lab. It is being tested, implemented, and shared through the STELAR ecosystem, helping both technical and non-technical users understand and work with their data more meaningfully.
Tech Brief #7: Correlation Detective: Multivariate Discovery
Our first tech brief, written by Jens d’Hondt, PhD candidate at TU/e, and Dr Odysseas Papapetrou, associate professor at TU/e, explores the importance of identifying complex correlations in data – not just between two variables, but across many.
Their work introduces Correlation Detective, a Java library that makes it possible to detect meaningful relationships across multiple variables, even in streaming or approximate contexts. This is a critical capability in fields like climate research, healthcare, or finance, where relationships are rarely simple or linear.
Correlation Detective goes beyond typical pairwise analysis. It can detect complex patterns, such as those involving averages or extremes across combinations of variables. And it does so quickly, even when datasets are large or constantly updating.
This means analysts can spot trends and anomalies earlier, with less computational strain. What good are data insights if they arrive too late or get lost in noise?
Tech Brief #8: Synopses to the rescue!
The second tech brief comes from Wieger R. Punter, a PhD candidate at TU/e, and it shifts the conversation from correlation to approximation – a topic that often raises questions. Can we really trust approximate data structures? Are they just shortcuts, or are they tools in their own right?
Wieger explains that approximation is not about sacrificing accuracy. It is about recognising the limits of memory and processing power, and working within those constraints. His brief introduces the concept of data synopses – small, representative samples or summaries that allow fast queries, even when full datasets are too large to process efficiently.
Different use cases require different types of synopses. Some are based on sampling (like reservoir sampling), others on frequency estimation (like histograms), and some use probabilistic approaches (like sketches). All offer ways to answer common questions with speed and reliability – whether you are measuring network traffic or monitoring environmental sensors.
For data practitioners working with real-time systems or limited resources, these tools are not just helpful. They are essential.
Making AI more usable, one brief at a time
These latest briefs reflect STELAR’s broader aim: to make AI tools more practical, efficient, and transparent. Correlation Detective helps users uncover deeper patterns. Approximation techniques support fast, cost-effective answers. Together, they point to a future where smarter data handling is not a luxury – it is a requirement.
Missed our previous tech briefs? You can find them here:
- Tech Briefs: Latest Trends in Data and AI
- Tech Briefs Series: Exploring Bias-Aware Innovations
- New Tech Briefs Released: AI & Knowledge Graph Advances
Follow us on LinkedIn or read our Blog for more updates, briefs, and behind-the-scenes stories from the STELAR project.
