Semantically Enhancing OLAP Cubes: Integrating SPARQL and SQL for Next-Generation Data Publication & Business Intelligence
Session Overview
In an era where data is not just an asset but the backbone of decision-making, traditional Business Intelligence (BI) tools like Microsoft Power BI have offered a gateway to insights with their user-friendly interfaces and powerful analytics capabilities. However, the challenge of deep, meaningful data integration—where data is not only aggregated but understood in its relational and semantic context—remains largely unmet. This session dives into the transformative potential of RDF technology in addressing this gap by semantically enriching OLAP (Online Analytical Processing) data. RDF's strength lies in its ability to make data comprehensible to both humans and machines, thereby facilitating a more nuanced understanding and interaction with information.
In our session, we will explore:
The process of semantically lifting OLAP cubes into RDF, enabling data to transcend its tabular constraints and be published and visualized with unprecedented clarity and flexibility.
The dual querying capabilities through SPARQL and SQL via the Ontop framework, illustrating how even users of mainstream BI tools like PowerBI, Tableau, and Metabase can benefit from enhanced data integration and interpretation.
Strategies to scale these semantic enhancements across billions of data columns using open-source technologies, breaking the barriers of volume and complexity.
The possibilities unlocked by properly mapped dimensions across datasets, paving the way for insights that are not just deeper but also broader and more interconnected.
This session aims to illuminate the path towards a future where BI is not just about generating reports and dashboards but about fostering a deeper, more intuitive understanding of data landscapes.
Target Audience
Data engineers, data architects, Open Data publishers, BI developers, and IT managers who are involved in data integration, publication, management, and analytics.
Desired Feedback
We are looking for feedback to refine our approach and better understand its potential. We're interested in hearing about your experiences with using RDF for OLAP cubes, any challenges you've had with non-RDF systems that you think RDF could solve, and your general interest in our methodology and the open source tools we use.
Speaker Details
Benjamin Cogrel, CTO Ontopic
Adrian Gschwend, CEO Zazuko
Recording Consent
YES
Workshop Potential
YES
Visual Aid for Social Media
We'd love to feature your session in our social media promotion. Please attach a picture or screenshot related to your talk. Ensure there's no confidential information displayed. Images should be high-resolution and visually engaging.
Talk Title
Semantically Enhancing OLAP Cubes: Integrating SPARQL and SQL for Next-Generation Data Publication & Business Intelligence
Session Overview
In an era where data is not just an asset but the backbone of decision-making, traditional Business Intelligence (BI) tools like Microsoft Power BI have offered a gateway to insights with their user-friendly interfaces and powerful analytics capabilities. However, the challenge of deep, meaningful data integration—where data is not only aggregated but understood in its relational and semantic context—remains largely unmet. This session dives into the transformative potential of RDF technology in addressing this gap by semantically enriching OLAP (Online Analytical Processing) data. RDF's strength lies in its ability to make data comprehensible to both humans and machines, thereby facilitating a more nuanced understanding and interaction with information.
In our session, we will explore:
This session aims to illuminate the path towards a future where BI is not just about generating reports and dashboards but about fostering a deeper, more intuitive understanding of data landscapes.
Target Audience
Data engineers, data architects, Open Data publishers, BI developers, and IT managers who are involved in data integration, publication, management, and analytics.
Desired Feedback
We are looking for feedback to refine our approach and better understand its potential. We're interested in hearing about your experiences with using RDF for OLAP cubes, any challenges you've had with non-RDF systems that you think RDF could solve, and your general interest in our methodology and the open source tools we use.
Speaker Details
Recording Consent
YES
Workshop Potential
YES
Visual Aid for Social Media
We'd love to feature your session in our social media promotion. Please attach a picture or screenshot related to your talk. Ensure there's no confidential information displayed. Images should be high-resolution and visually engaging.