Zen and the art of data structures: From self-tuning to self-designing data systems
Designing data systems is something few people understand, and it's very hard and costly. But that, too, could be automated, says new research from Harvard, and we're about to start seeing it in real life.
Read More →Radio data and the future of broadcasters: Using attribution analysis to measure consumer behavior
Is it possible to determine how effective radio advertising really is? TagStation says yes, using a method called attribution analysis, and this may be key for the future of broadcasters.
Read More →The best programming language for data science and machine learning
Hint: There is no easy answer, and no consensus either.
Read More →Data-driven software development in the cloud: Trends, opportunities, and threats
Software development has been fundamentally changing. It's following the data and going to the cloud. What should organizations be aware of to make the most of it?
Read More →GraphQL for databases: A layer for universal database access?
GraphQL is a query language mostly used to streamline access to REST APIs. Now, a new breed of GraphQL implementations wants to build an abstraction layer for any database on top of GraphQL, and it seems to be catching up.
Read More →Open or closed? On graph database access, query languages, community building, and TigerGraph
Having an entry path, as well as a strong community, is important for any solution, and graph databases are no different. Following latest developments in graph query languages, TigerGraph is changing its strategy. How will this affect the domain? If you’ve been watching the graph database space, you probably know TigerGraph. It’s one of the […]
Read More →Business analytics: The essentials of data-driven decision-making
Data shows that data-driven organizations perform better. But what does it take to get there?
Read More →NBA analytics and RDF graphs: Game, data, and metadata evolution, and Occam’s razor
Three-point shooting, Steph Curry, and coming up with stories. If you feel like doing your own analysis to investigate hypotheses or discover insights at any level, RDF graph's got your back. Case in point: The NBA.
Read More →Human in the loop: Machine learning and AI for the people
HITL is a mix and match approach that may help make ML both more efficient and approachable.
Read More →The road to automation, the joy of work, and the ‘Jen problem’
How do we get to the point where technology is the infrastructure firms run on, and what happens when we do?
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