
Last year, the NYT shined a light on big data’s “janitor” problem – that data scientists and business intelligence pros spend too much time cleaning, not evaluating data. But how big of […]
Last year, the NYT shined a light on big data’s “janitor” problem – that data scientists and business intelligence pros spend too much time cleaning, not evaluating data. But how big of […]
Here is an actual LinkedIn sponsor ad: “In just 12 weeks, you’ll learn the tools, techniques, and fundamental concepts you need to know to make an impact as a data scientist. During […]
Like Alan Turing’s vision to create smarter machines to crack the Enigma Code in World War II, we now sit at a critical juncture to solve the significant pain and expense of […]
Be prepared to Wrangle – When dealing with “big data” (#bigdata), about 2/3 of you project time is spent getting access to the data, getting the right data, preprocessing the data, and […]
I know, that is pretty confusing. What we have, however, is a distorted, all-over-the-place, inadequate, confusing, and too broad a definition of “data scientist”. I do not know where we went wrong, […]
Q: For readers unfamiliar with Tamr, how would you describe the company and its value proposition? A: Businesses have mission-critical questions to ask. They have the data assets they need to answer them. They’ve […]
Data chores — gathering, cleaning, and sorting — can be done by an outside firm, so your employees can turn their attention to analytics. Most enterprises are about five years into their […]
Data scientists spend 80% of their time convert data into a usable form. There are many tools out there to help and I will go over some of the most interesting. There […]