What not to do as a data scientist, the effectiveness of infographics, and the growth of BI in the cloud.
- By Lindsay Stares
- April 20, 2017
Google’s next innovation, 5 steps to manage your big data, and how big data analytics can be used to improve food delivery.
- By Lindsay Stares
- April 18, 2017
The market for machine learning grows, automation expands on Wall Street, and how machine learning may help treat depression.
- By Lindsay Stares
- April 13, 2017
Both humanitarian aid workers and climate researchers are seeking answers in data science; meanwhile, Google is moving in on the enterprise cloud market.
- By Lindsay Stares
- March 21, 2017
Companies with customers, supply chains, partners, and offices in multiple countries must understand how cross-border data restrictions affect cloud computing policy.
- By William McKnight
- March 17, 2017
Financial services can benefit from the many competitive use cases enabled by artificial intelligence and machine learning, but adoption has been slow.
- By Brian J. Dooley
- March 13, 2017
O'Connell spoke recently about his work "at the confluence of analytics software and customers' business problems" and what he sees as the future of AI solutions.
- By James E. Powell
- March 10, 2017
Data availability for the visually impaired, good cloud security practices, and SQL’s importance for data science.
- By Lindsay Stares
- March 9, 2017