Alibaba Blinks: Building an open source, data-driven cloud empire in real-time
Acquiring data Artisans, the vendor leading development of open source Apache Flink framework for real-time data processing, is the latest move from Alibaba. Where does this fit in Alibaba's strategy to grow its cloud?
Read More →The rise of Kubernetes epitomizes the transition from big data to flexible data
Can a platform conceived to support running ephemeral applications become the operating system of choice for running data workloads in the multi-cloud and hybrid cloud era? Looks like it, but we're not just there yet.
Read More →Just another Cyber Monday: Amazing Amazon and the best deal ever
When you get something at 80% off on Amazon, who do you think wins — you or Amazon? If you think that’s a strange question, you ain’t seen nothing yet. Maybe it’s time we re:Invent some things. But, how can possibly getting a huge discount be bad? It’s not, if you actually need what you’re buying, and […]
Read More →From big data to AI: Where are we now, and what is the road forward?
It took AI just a couple of years to go from undercurrent to mainstream. But despite rapid progress on many fronts, AI still is something few understand and fewer yet can master. Here are some pointers on how to make it work for you, regardless of where you are in your AI journey.
Read More →Processing time series data: What are the options?
Get your data from everywhere you can, anytime you can, they said, so you did. Now, you have a series of data points through time (a time series) in your hands, and you don't know what to do with it? Worry not, because there's a bunch of options.
Read More →Knowledge graphs beyond the hype: Getting knowledge in and out of graphs and databases
What exactly are knowledge graphs, and what's with all the hype about them? Learning to tell apart hype from reality, defining different types of graphs, and picking the right tools and database for your use case is essential if you want to be like the Airbnbs, Amazons, Googles, and LinkedIns of the world.
Read More →The past, present, and future of streaming: Flink, Spark, and the gang
Reactive, real-time applications require real-time, eventful data flows. This is the premise on which a number of streaming frameworks have proliferated. The latest milestone was adding ACID capabilities, so let us take stock of where we are in this journey down the stream — or river.
Read More →AI chips for big data and machine learning: Hard choices in the cloud and on-premise
How can GPUs and FPGAs help with data-intensive tasks such as operations, analytics, and machine learning, and what are the options?
Read More →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.
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