by Angela Guess Jessica Davis recently wrote in InformationWeek, “Looking to break into the field of data science or to gain the skills to be able to transition to this field in the future? Interested in becoming a data analyst and perhaps eventually moving into a data scientist role? Then you’re probably doing some research […]
Top 20 Hottest Data Management Posts Year-to-Date 2016
It has become a semi-annual tradition here at DATAVERSITY® to publish our top twenty most popular data management content year-to-date. Though we monitor topic popularity daily, we like to stop every six months or so to do a deep dive into what subscribers are reading. What’s hot and trending? Our top twenty includes Data Blogs, […]
Big City, Big Data: Data Science Education at Columbia University
Columbia University’s Data Science education programs are fairly new, with the Data Science Institute founded in 2012. The program seeks to take an interdisciplinary approach, drawing on more than 200 faculty from the nine schools that make up the university. The classes were intentionally designed especially for these programs, not pulled from existing courses. Research […]
Making Your Data Progressively Smarter
Click here to learn more about author James Kobielus. Data is data. It’s not inherently dumb or smart. What matters is whether your data, be it large or small, contributes to smarter decisions. How can you leverage your big-data resource so that it drives smarter decisions? Last year, DATAVERSITY published this thought-provoking Dataversity article in which they stated […]
How Big Data Systems Can Empower You to Ask New, Better Questions
by Angela Guess Roy Wilds recently wrote in Information Management, “You think you know what’s in your data. But there may be a lot more there than you realize. The combination of big data and modern data science can empower you to ask questions in entirely new ways, and uncover answers locked away in your […]
3 Reasons Data Science Projects Fail
by Angela Guess Isaac Roseboom recently wrote in Dataconomy, “The rise of data science in the last decade has been driven by the ease of access to deep data and significant reductions in the costs associated with processing it. These days anyone with a credit card can now setup a cloud-based data warehouse and tracking […]
Expanding Data Science Skills to Meet the Needs of Big Data
by Angela Guess Aaron Auld recently wrote in ITProPortal, “Today data scientists can be deprived of their strengths when moving to larger datasets – datasets in the realm of ‘big data’ – because large scale tools are too inflexible to support the data science style of working. Michael Stonebreaker, winner of the Turing Award 2014. […]
A Comparative Roundup: Artificial Intelligence vs. Machine Learning vs. Deep Learning
A 1969 McKinsey article claimed that computers were so dumb that they were not capable of making any decisions. In fact they said, it was human intelligence that drives the dumb machine. Alas, this claim has become a bit of a “joke” over the years, as the modern computers are gradually replacing skilled practitioners in […]
The Case for More Domain Experts in Data Science
by Angela Guess Kalev Leetaru recently wrote in Forbes, “As I’ve come to work with an ever-widening swath of the data sciences and “big data” communities, I have been struck by how narrowly focused much of its practitioner base is on statistics and computational expertise as opposed to a solid understanding of the domain being […]
How You Know Insight as a Service is Right for Your Enterprise
Click here to learn more about author Luca Scagliarini. Businesses are buying all kinds of data and data analytics solutions but they may still fail to meet their business goals. Increasingly, vendors and professional services firms are offering Insights as a Service (IaaS), which can be part of the cloud stack or a new, pay-for-answers economic model. Let me […]