In this article, we’ll make sense of data science for those unacquainted with the field and outline a series of 7 easy steps to get up to speed with the technology. In doing so, we’ll highlight the integral steps in the “data science process,” so you can get a good grasp of how data science works and how it is of value to enterprises seeking to maximize the value of their data assets.
The presentation below by Alex Smola is “Personalization and Scalable Deep Learning with MXNET” from the MLconf San Francisco, 2016. User return times and movie preferences are inherently time dependent. In this talk, Alex shows how this can be accomplished efficiently using deep learning by employing an LSTM (Long Short Term Model). Moreover, he shows how to train large scale distributed parallel models using MXNet efficiently.
The annual State of Analytics Adoption Report by our friends at Logi Analytics provides insights for executives, product managers, and technology leaders on how broadly and deeply users are adopting business intelligence and analytics tools. The 2017 survey respondents included members of IT teams who provide analytics tools to end users, as well as the end users of BI and analytics tools.
NewVantage Partners, strategic advisors in big data and business innovation to Fortune 1000 businesses, has released the results of its 2017 5th Annual Big Data Executive Survey, entitled “Big Data Business Impact: Achieving Business Results through Innovation and Disruption.” The 2017 Big Data Executive Survey reports what executives from 50 Fortune 1000 firms see as the key factors driving big data adoption, investment – and success.
In this talk from Spark Summit East 2016, Prasad Chalasani explores some of the challenges that arise in setting up scalable simulations in a specific application, and share some solutions and lessons learned along the way, in the realms of mathematics and programming.
451 Research’s latest Voice of the Enterprise: Internet of Things (IoT) Organizational Dynamics survey of nearly 1,000 enterprise IT buyers worldwide reveals that 71% of enterprises are gathering data for IoT initiatives today. This is a three percentage point increase from the previous quarter’s Voice of the Enterprise: IoT Workloads and Key Projects survey.
In this TEDx presentatin, Reuben Vendeventer’s talk is pitched towards students, but it’s useful for business people too. The value in Vendeventer’s talk is his orientation towards data and the information age. He conceptualizes our knowledge of DNA as data points. This kind of reorientation is a solid start for any learner’s relationship with the data behind business intelligence.
In this TEDxVancouver presentation, Jer Thorp’s discussion is stellar because it frames the story of how data can tell our stories. His project, openpaths.cc, tracked (willing) participants’ iPhone location data, his own included. His take on his own data’s story—matching each location with his career journey.
Emerging Technologies Like Advanced Analytics, Machine Learning and IoT Help Revolutionize Public Sector Agencies
Advanced analytics and other emerging technologies are revolutionizing the way governments and public service agencies are trying to address citizen demands, helping to overcome persistent challenges such as regulatory compliance, outdated legacy IT infrastructures and organizational cultures, according to a new research report from Accenture.
The “data” industry continues on its upward trajectory into 2017 and for the foreseeable future. Our friends over at Indeed (we’re the world’s largest job search engine) provides a general sense for how the market for data related jobs has shifted.