Category: Big Data & Data Science

It’s a Tuesday afternoon, the office is bustling, your servers are down and your tech team is stumped. The phone rings – the call you’ve been dreading. Your data and critical servers have been compromised. The attackers are demanding a hefty fee to undo the damage. It’s a scenario that has played out thousands of […]

Getting a big data project in place is a tough challenge. But making it deliver results is even harder. That’s where artificial intelligence comes in. By integrating artificial intelligence into your big data architecture, you’ll be able to better manage, and analyze data in a way that provide a substantial impact on your organization. With big data getting even […]

Intel’s distribution of Python, created in collaboration with Anaconda, is billed by the hardware giant as a distribution created for performance. Specifcally, the numerical performance demanded by scientific research and machine learning. Claims are bandied about referring to Python that executes at machine-language speeds, but does Intel Python really deliver? I won’t use the word […]

When historians study contemporary notions of data in the early 21st century, 2018 might well be a landmark year. In many ways this was the year when Big and Important Issues – from the personal to the political – began to surface. The techlash, a term which has defined the year, arguably emerged from conversations and […]

As mentioned previously, several important RevoScaleR functions include provisions for transforming data within the function itself, rather than require separate steps in addition to the function call. This is advantageous, since it means that large datasets can be read once instead of having to be read repeatedly by several functions. rxImport, rxDataStep, and rxSplit support […]