Navigating the AI transition in marketing
IEEE Big Data 2025: the shift from scale to smart
IEEE Big Data 2025 signals a shift to secure, hybrid intelligence. CTO Sabri Skhiri unpacks the engineering reality from the conference: the practical shift to embeddings, the real need for security layers, and the limitations of AI agents in production.
How sales receipt data contributed to review marketing strategy
A sales receipt contain a wealth of primary data on shopping habits, product, and retailer information. Find out how we used this marketing gold mine to support a hyper market in its marketing efforts.
Navigating the future of AI governance
Beyond the obligation for high risk systems to conduct a data protection impact assessment, the value added of impact assessments for IA models would rely on the risks covered, the economic dimension of such assessment and its interest in terms of IA governance. The panel at CPDP conference discuss the content and benefits of user-centric impact assessments for IA across the value chain.
How a postal operator made the most of computer vision to create new sources of revenues
How computer vision helped an international and domestic postal operator create new sources of revenues capturing images of road signs is the story we’re telling you here.
Unlocking business value with insights from the PETs London conference
In March 2024, our CTO travelled to London for the Privacy Enhancing Technologies (PETs) Summit. In this article, we distil the key themes and insights shared during the conference, shedding light on the business implications of PET adoption and the delicate balance between overhead, value, and regulatory compliance.
Tech Insights from the PET Summit 2024
The recent Privacy Enhancing Technologies (PETs) London Conference convened stakeholders across Legal, IT, and various business domains to delve into the evolving data privacy and security landscape. Here, we distil the key themes and insights shared during the conference, shedding light on the interesting talks.
Researchers get insights in minutes instead of hours
An international pharmaceutical company sought to unlock the value of its data but lacked the expertise to build a fast, tailored platform, critical for reducing experiment processing from a full day to under an hour.
SANGEA: Scalable and Attributed Network Generation
In this paper, we present SANGEA, a sizeable synthetic graph generation framework that extends the applicability of any SGG to large graphs. By first splitting the large graph into communities, SANGEA trains one SGG per community, then links the community graphs back together to create a synthetic large graph.
Data driven- IT operations in banking
A Belgian bank sought to become data‑driven by unifying fragmented IT data, automating reporting, and building secure pipelines to deliver reliable KPIs, faster decisions, and GDPR‑compliant insights across its IT operations.
The 2023 Big Trends of Privacy Enhancing Technologies
In March 2023, our research director Sabri Skhiri travelled to London to attend the Privacy Enhancing Technologies Summit 2023. In this article, he dives into the significance of PETs, shares his insights, and summarises the main trends from the summit.
Tech Insights from the PET Summit 23
In March 2023, our research director Sabri Skhiri travelled to London to attend the Privacy Enhancing Technologies Summit 2023, dedicated to PETs and their uses (enhance data security, facilitate compliance, and create value).
Data-driven microbiome medicines for oncology
From microbiome sequencing to predictive models driving immunotherapy innovation.
How data science can make pandemic predictions better
How moving to a more complete approach based on individual health behaviour, health state and daily habits gave a global pandemic prediction model more accuracy and became a decision-making tool for governments to improve vaccinations in their country.
Tech Insights from the PET Summit 2022
In April 2022, our research director Sabri Skhiri travelled to Zurich to attend the Privacy Enhancing Technologies Summit 2022, dedicated to PETs and their uses (enhance data security, facilitate compliance, and create value). In this article, he gives you his opinion about PETs’s’ big trends, and a selection of his favourite talks.
Anomaly Detection: How to Artificially Increase your F1-Score with a Biased Evaluation Protocol
Anomaly detection is a widely explored domain in machine learning. Many models are proposed in the literature, and compared through different metrics measured on various datasets. The most popular metrics used to compare performances are F1-score, AUC and AVPR...
Webinar - Improve Traffic Flow with AI
Unlocking 25 Years of R&D data through graph visualization
A global oil and gas company’s R&D hub amassed decades of complex materials and chemical data, but limited data expertise made it hard for scientists to access, explore, and extract meaningful insights from these siloed datasets
A Combined Rule-Based and Machine Learning Approach for Automated GDPR Compliance Checking
The General Data Protection Regulation (GDPR) requires data controllers to implement end-to-end compliance. Controllers must therefore ensure that the terms agreed with the data subject and their own obligations under GDPR are respected in the data flows from data subject to controllers, processors and sub-processors (i.e. data supply chain).
TopoGraph: an End-To-End Framework to Build and Analyze Graph Cubes
In this paper, we introduce TopoGraph, an end-to-end framework for building and analyzing graph cubes. TopoGraph extends the existing graph cube models by defining new types of dimensions and measures and organizing them within a multidimensional space that guarantees multidimensional integrity constraints.
Tech Insights from Flink Forward 2019
Early October 2019, 6 EURA NOVA engineers travelled to Berlin to attend the Flink Forward Conference, dedicated to Apache Flink users and stream processing communities.
Data Mining and ML Techniques Supporting TBS Concept Deployment
The paper presents two methods to allow air traffic controllers to deliver separation minima accurately and safely, on the basis of time intervals instead of distances.
Graph BI & Analytics: Current State and Future Challenges
The paper presents the state of the art of graph BI & analytics, with a focus on graph warehousing. We survey the topics of graph modelling, management, querying, and processing in graph warehouses.
An analytics-aware conceptual model for evolving graphs
Graphs are ubiquitous data structures commonly used to represent highly connected data. Many real-world applications, such as social and biological networks, are modeled as graphs. To answer the surge