"Data Rules" is a book about data, but not just about big data crunching. A book about the relationship of data with economic institutions and society, but also about the interplay with data technologies by which data are being generated and processed. A book that is critical, but not ideological.

This is how Jannis Kallinikos describes "Data Rules: Reinventing the Market Economy", a book co-authored by himself and Cristina Alaimo and recently published by The MIT Press.

Jannis Kallinikos is Full Professor of Organization Studies and the CISCO Chair in Digital Transformation and Data Driven Innovation at LUISS University, Rome.

This is where we met to talk about the key concepts in "Data Rules":

• Understanding data generation and use
• How data is breaking boundaries
• Platforms and choice
• The illusion of objectivity
• Algorithms, agency and surveillance
• From market and design rules to data rules

Article published on Orchestrate all the Things: https://linkeddataorchestration.com/2024/07/01/data-rules-from-interoperability-to-commensurability/

What is a universal semantic layer, and how is it different from a semantic layer? Are there actual semantics involved? Who uses that, how, and what for?

When Cube Co-founder Artyom Keydunov started hacking away a Slack chatbot back in 2017, he probably didn't have answers to those questions. All he wanted to do was find a way to access data using a text interface, and Slack seemed like a good place to do that.

Keydunov had plenty of time to experiment, validate, and develop Cube, as well as get insights along the way. We caught up and talked about all of the above, as well as Cube's latest features and open source core.

Article published on Orchestrate all the Things.

From better together to full native integration, Neo4j is creating an ecosystem around all major cloud platforms to provide graph-powered features for Generative AI and beyond.

As Neo4j just announced its partneship with Microsoft, we met with Chief Product Officer Sudhir Hasbe to talk about:

• What this partnership means for users and how it works
• How graph-powered generative AI aligns with cloud platform AI strategies
• Similarities and differences across them
• How Neo4j's strategy is shaping up, and when Databricks and Snowflake integration are coming.

For additional analysis and a writeup of the conversation, you can read the article published on Orchestrate all the Things: https://linkeddataorchestration.com/2024/03/27/neo4j-partners-with-microsoft-unfolds-strategy-to-power-generative-ai-applications-with-cloud-platforms-and-graph-rag/