In a previous blog, I explained how data science capabilities, massive parallel processing (MPP)
and usability improvements in data warehouse appliances can help the bottom line—and why old-fashioned architectures might not cut it. But what does that look like in practice?
Research firm Quark +
Information analytics has never been a “one size fits all” proposition. That applies to the hardware and software technologies organizations employ, the information being parsed and the goals of specific projects.
Data visualization techniques can give data scientists a vital tool for representing the data that analysts and line-of-business users need to make strategic decisions. Discover how a few simple considerations of a specific data set in a real-world use case enables data scientists to implement cost