In this special guest feature, Lauren Willison, Director of Admissions at Florida Polytechnic University, takes a critical look at the value of an advanced degree in big data in terms of job prospects and expected salary.
If you’re building or growing a data science team, the first reflex is to hire new talent. Before you do so, take a few moments to ask yourself the following questions.
Artificial intelligence is hot! So why not attend the upcoming AI World Conference & Expo in San Francisco, Nov. 7-9 to get a state-of-the-art look at what AI brings to the enterprise.
Please participate in our new audience survey on AI/machine learning/deep learning and give us your opinions about whether your company has any plans to become an AI Enterprise?
Our friends over at DataCamp have produced the “Become a Data Scientist in 8 Steps” infographic providing a view of the eight steps that you need to to through to learn data science. Some of these eight steps will be easier for some than for others, depending on background and personal experience, among other factors.
The water and wastewater industry is in transition to a digital revolution that has the potential to transform the industry from the use of data-driven technologies, with utility sector spending dwarfing the industrial market. This is according to a new report by Global Water Intelligence (GWI) that provides a detailed guide to the opportunities in this smart market.
In the TEDx video presentation below, Kevin Novak, Senior Data Scientist at Uber, provides a description and history of Uber and how Uber’s data hacking made their explosion possible.
In the video presentation below, courtesy of our friends over at GridGain, Eric Karpman shares how some of the world’s largest financial institutions use in-memory computing to address the challenges of high frequency trading.
In this video from the 2016 HPC User Forum in Austin, John Feo from PNNL presents: Why use Tables and Graphs for Knowledge Discovery System? “GEMS software provides a scalable solution for graph queries over increasingly large data sets. As computing tools and expertise used in conducting scientific research continue to expand, so have the enormity and diversity of the data being collected. Developed at Pacific Northwest National Laboratory, the Graph Engine for Multithreaded Systems, or GEMS, is a multilayer software system for semantic graph databases. In their work, scientists from PNNL and NVIDIA Research examined how GEMS answered queries on science metadata and compared its scaling performance against generated benchmark data sets. They showed that GEMS could answer queries over science metadata in seconds and scaled well to larger quantities of data.”
The insideBIGDATA Guide to Healthcare & Life Sciences is a useful new resource directed toward enterprise thought leaders who wish to gain strategic insights into this exciting new area of technology. The guide provides an overview of the utilization of big data technologies as an emerging discipline in healthcare and life sciences. It explores the characteristics of this business strategy and the benefits of leveraging big data technologies within these sectors. It also touches on the challenges and future directions of big data and analytics in the healthcare and life sciences industries.