Click here to learn more about author Ravi Shankar. Data is the new currency in this digital economy. Companies generate data during the normal course of their operations, analyze that data to gain intelligence about their business, and use that insight to tweak their operations to improve results; call it the data cycle. To protect such […]
Don’t Fence Me In: Tensions on the Data Science Frontier
Click here to learn more about author James Kobielus. Data scientists can be a stubborn, proud, and independent lot. In their hearts, they’re new-age prospects whose primary occupation is to uncover hidden veins of insight buried deep in data. Self-starting genius is a great thing, but it’s not what pays the bills. In the new […]
Where are We with Machine Learning?
Learn more about video blogger Stefan Groschupf. Over the course of the next few months we will be releasing insights in Machine Learning, the Cloud, and Big Data in this new video blog series presented by Stefan Groschupf, CEO of Datameer. Here’s Stefan’s first short video blog on “Where are We with Machine Learning?.”
How Cognitive Data Science Can Cure the Talent Shortage
Click here to learn more about author Sundeep Sanghavi. The Internet of Things and its interconnected approach has led to an overwhelming explosion of big data. About 6.4 billion connected devices are already in use today, and Gartner expects that number to reach 20.8 billion by 2020. This growth is big business; it’s estimated that […]
Vetting the Actual Science Behind Data Science
Click here to learn more about author James Kobielus. Everybody wants to rule the world–or, at the very least, discover the fundamental rules that rule the world. That’s why we have scientists. Statistical models are the heart of most scientific inquiry. In business applications, for example, data scientists often work with behavioral data that is […]
No Relief with Hadoop – Managing The Big Data Reality Gap
Click here to learn more about author Jon Bock. There has been much anticipation that businesses would find relief for their analytics headaches in Hadoop, the open source software for distributed processing and distributed storage of large data sets across clusters of commodity or cloud hardware. There is no doubt Hadoop systems can handle large […]
Web Scraping for Data Science — Part 2
Click here to learn more about author Steve Miller. Read Part 1 of this blog series here. Between R and Python, analytics pros are covered on most data science bases R-Python. In last month’s blog, I discussed simple webscraping using Python in a Jupyter notebbok, the nifty css-generating tool SelectorGadget, and the Python XML and HTML handling package lxml. […]
The API Economy: A Big Ball of CRUD
Click this link to learn more about the author Dave Duggal. Quote: “The use of APIs has exploded with the growth of distributed computing, driven by the popularity of the Web, Cloud and now, the Internet of Things (IoT)” Back in 1999 an academic paper, “The Big Ball of Mud” exposed fundamental limitations of ‘modern’ software […]
Selling the Value of Data Science, Governance or Analytics
Click here to learn more about Kimberly Nevala. I’ve recently participated in a number of executive forums on the rewards and realities of creating data-savvy and analytically-enabled cultures. Interestingly, one key theme comes up repeatedly in audience Q&A: how to make the case? Seems simple enough, but this step often causes those who understand the […]
Web-Scraping for Data Science – Part 1
Click to learn more about Steve Miller. Scraping data from the web is a task that’s essential to the data scientist’s hacking portfolio. The complexity of work ranges from sophisticated crawling that mandates understanding the structure of dynamic web pages along with command of css and/or xpath, to the more mundane “just grabbing a table […]