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?
Read More →From Brexit to Trump: How organizations can use data to prepare for and respond to political events
Politics and data do mix, apparently, so we try to count the ways.
Read More →How Trifacta is helping data wranglers in Hadoop, the cloud, and beyond
Trifacta is known for doing one thing, and doing it well: data wrangling. Because of this, the company has an informed, data-driven view on the big data and not-so-big data market. Trifacta's insights have driven its latest product release, but are also relevant to draw a big picture of big data.
Read More →IBM’s Watson does healthcare: Data as the foundation for cognitive systems for population health
Watson is IBM's big bet on AI, and healthcare is a prime domain for present and future applications. We take an inside look at Watson, why and how it can benefit healthcare, and what kind of data is used by whom in this process.
Read More →Open for business: How public data in private places works for AWS, publishers and users
Most people know Amazon Web Services as the biggest player in the cloud, but not as many know that AWS is also big on open data and onto a business model that can help everyone get value out of it. Jed Sundwall, AWS Global Open Data Lead, discusses.
Read More →Samsung’s acquisition of Viv brings up questions about massive-scale AI
The war for mainstream AI dominance is raging. The latest episode was last week's announcement of Samsung acquiring Viv, a hitherto under the radar startup working on building the next Siri. We take the opportunity to ponder on questions related to massive-scale AI.
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.
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