The National Institute of Standards and Technology (NIST) is attempting to create standards for Big Data. They just released the NIST Big Data interoperability framework, which is a huge set of documents aimed at creating standards around everything in big data from definitions to architectures.
Big Data Definitions
In case you are wondering, and I know you are, what are the definitions. The framework includes many more definitions.
Big Data consists of extensive datasets – primarily in the characteristics of volume, variety, velocity, and/or variability – that require a scalable architecture for efficient storage, manipulation, and analysis.
Data science is the empirical synthesis of actionable knowledge from raw data through the complete data lifecycle process.
Don’t like the definitions? Great, NIST would love to hear your opinions/comments. Comments are being collected until May 21, 2015.
Sound appealing? Probably not! Unfortunately, this is the sad reality for many children in Sub-Saharan Africa. Even worse, this sad reality is only for those children lucky enough to even attend school. In the world today, there are 58 million out of school children, and 43% of those children will never start attending school.
Sense has launched to the public today, March 18, 2015. Sense is an online data science platform providing you the capability to easily perform your entire data science workflow via a browser. No need to provision new servers or install software, just click “New Project” and start your analysis. The Sense platform includes the following features:
Languages: R, Python, Julia, SQL
Simple collaboration for teams
Easily Scale up or down with just the click of a mouse
Notifications for completion of long running tasks
An on-premise Enterprise version
I have been one of the early beta-testers for Sense, and I have previouslywritten about using the platform. I really like the platform. I find it easy, intuitive, and clean. Plus, I love being able to run all my analysis with just my chromebook. So, go signup and please feel free to follow me at sense.io/ryanswanstrom as I am sure to be adding some new analysis.
Below is a video with an expanded introduction to the Sense Platform.
Ben Wellington gives an excellent Ted Talk on open data. He argues that cities need to make more of an effort to release data in a standardized and machine-readable format. This could help cities be safer and fiscally responsible. He is hoping New York City sets the standards for open data for cities. As a bonus, he is a wonderful story teller.
Have you ever wondered what the deal was behind all the hype of “big data”? Well, so did we. In 2014, data science hit peak popularity, and as graduates with degrees in statistics, business, and computer science from UC Berkeley we found ourselves with a unique skill set that was in high demand. We recognized that as recent graduates, our foundational knowledge was purely theoretical; we lacked industry experience; we also realized that we were not alone in this predicament. And so, we sought out those who could supplement our knowledge, interviewing leaders, experts, and professionals – the giants in our industry. What began as a quest for the reality behind the buzzwords of “big data” and “data science,” The Data Analytics Handbook, quickly turned into our first educational product of our startup Leada (see www.teamleada.com). Thirty plus interviews and four editions later, the handbook has been downloaded over 30,000 times by readers from all over the world In them, you’ll discover whether “big data” is overblown, what skills your portfolio companies should look for when hiring a data scientist, how leading “big data” and analytics companies interview, and which industries will be most impacted by the disruptive power of data science. We hope you enjoy reading these interviews as much as we enjoyed creating them!