Disrupting insurance: data-driven customer value
Why hasn't the insurance business been disrupted yet, and how could data be used to do this? Atidot has a go at addressing those questions.
Read More →Devs are from Mars, Ops are from Venus: Can analytics bridge the gap?
Despite what they'd have you believe, Devs and Ops don't always get along nicely. Pepperdata and LinkedIn think data and analytics may be the way to educate and show the impact of code running in production.
Read More →Staying agile: data-driven IT operations
Would you like to have an end-to-end picture of your IT operations, but are lost in translation among a myriad monitoring solutions and metrics? Your monitoring should be as agile as your operations, and OpsDataStore says it can help you get there.
Read More →Digital transformation as a data-centric service
Is digital transformation something you can just buy into? No, but it is a data-centric process, and having the right products and people in place makes all the difference, according to Stratio.
Read More →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 →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 →Birst-ing into mainstream: Machine Learning meets Semantics in a networked world
Birst is one of the poster children of self-service analytics. Convergence and democratization are the key themes underlying Birst's new release out today, as Birst is trying to balance self-service with enterprise requirements, and making a case for some of the industry's defining trends while at it.
Read More →Data to analytics to AI: From descriptive to predictive analytics
Artificial Intelligence (AI) seems to be the buzzword du jour for organizations, but this is not an obvious or straightforward transition even for those building advanced products and platforms. Many organizations are still struggling with digital transformation to become data-driven, so how should they approach this new challenge?
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?
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