
Tag: big data
Product teams should not feel left behind when it comes to analytics. Funnel analytics have been a marketer’s best friend for years now, while one division over, product managers have clamored to make sense of the terabytes of data companies have on product and feature usage. Read more…
“An opportunity of a lifetime.” Many businesses would not describe the COVID-19 pandemic in these words, but forward-thinking leaders are doing just that. Framing a crisis as an opportunity to reinvent their organizations has been essential for these leaders. Read more…
Trifacta today launched what might be the world’s first cloud designed specifically for data engineering. Running on AWS, Microsoft Azure, and Google Cloud, the new Trifacta Data Engineering Cloud provides a place for data engineers to improve the quality of data before its sent to downstream analytics, BI, and machine learning systems. Read more…
Recent failures of electric grids in Texas and California have highlighted the difficulties that energy companies and regulators face in ensuring the delivery of reliable and affordable power while simultaneously switching to less-polluting energy sources. Read more…
When the economy went into lockdown from COVID last March, consumer demand shifted practically overnight, throwing retailers and their carefully planned supply chains into disarray. Like many retailers, CVS Health suffered from the turmoil. Read more…
It can be difficult to understand exactly what’s going on inside of a deep learning model, which is a real problem for companies concerned about bias, ethics, and explainability. Now IBM is developing something called AI FactSheets, which it describes as a nutrition label for deep learning that explains how models work and that can also detect bias. Read more…
While every organization of a certain age is saddled with legacy technology, very few can afford to upgrade to meet modern needs. Instead, successful organizations must build cross-enterprise data strategies that incent data sharing while allowing the organizations to continue to evolve their systems. Read more…
These are heady days in data science and machine learning (DSML) according to Gartner, which identified a “glut” of innovation occurring in the market for DSML platforms. From established companies chasing AutoML or model governance to startups focusing on MLops or explainable AI, a plethora of vendors are simultaneously moving in all directions with their products as they seek to differentiate themselves amid a very diverse audience. Read more…
Having a large stockpile of data is still a prerequisite for advanced analytics and AI. But companies building AI models increasingly are finding that artificially created data can be just as good as the real thing. Read more…