Googling prescriptive analytics: YouTube recommendations and the analytics continuum
Understanding prescriptive analytics is complicated, let alone implementation. Would turning to Google help? Seeing how it works for Google raises questions, but may also lead to some answers.
Read More →Big Data, Crystal Balls and Looking Glasses: Reviewing 2016, predicting 2017
End-of-year reviews are boring — and everyone does them. Predictions are boring — and they are hard. Of course, this is different — because big data.
Read More →Why finance craves big data: A perfect storm of disruption and opportunity
The financial services domain, where real-time is measured in milliseconds, holds particular interest for big data applications and vendors for a number of reasons: architecture, regulation, transparency, decision-making, and the need for speed.
Read More →Predictive analytics and machine learning: A dynamic duo
Predictive analytics and machine learning are seen as the pair of tools to save the day for most organizations currently. We try to de-mystify both, taking a look at what they are, how they work, and what they are good for.
Read More →Out of the Hadoop box: SQL everywhere and AtScale
AtScale has made a name for itself by providing an access layer on top of Hadoop that enables it to be used directly as a data warehouse. AtScale is now announcing support for Teradata DW and Google Dataproc and BigQuery, offering what it calls a Unified Analytics Platform. Why this move now, how does it work and what does it mean?
Read More →To the cloud, big data sisters and brothers, to the cloud
While reports of big data's death have been greatly exaggerated, the skepticism is not unwarranted. The cloud may have some of the answers, but it won't solve all of big data's problems.
Read More →IBM DataWorks, a holistic approach to leveraging data
This week at Strata, IBM unleashed a series of announcements and presentations about its Project DataWorks. DataWorks takes some deciphering to figure what it is exactly: a (line of) product(s), a methodology, or a strategic initiative. Spoiler alert: it's all of the above.
Read More →I got 99 data stores and integrating them ain’t fun
Data integration may not sound as deliciously intriguing as AI or machine learning tidbits sprinkled on vanilla apps. Still, it is the bread and butter of many, the enabler of all things cool using data, and a premium use case for concepts underpinning AI.
Read More →What IBM, the Semantic Web Company, and Siemens are doing with semantic technologies
Defining semantics is a matter of semantics, not less so in the Big Data space.
Read More →MarkLogic, dual-wielding its way through transactional and analytical workloads
Is dealing with transactional and analytical workloads in a single database a pipe dream? Not according to MarkLogic, which has its own way of taking on both.
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