The Doctor Is In: The Role of the Data Scientist for Analyzing Big Data
No profession is getting more attention these days than that of the “data scientist.” Data scientists have made the covers of business magazines and are practically rock stars at online companies such as Google, Facebook, and LinkedIn.
Organizations in many industries are desperately seeking to hire the best and the brightest to help them explore large volumes of data, think analytically in the context of business questions, and arrive at unique insights that will improve profitability and competitiveness. The activities and expertise of a data scientist can vary considerably, but they include data mining, predictive model development and scoring, statistical analysis, optimization, Hadoop programming, visualization, and more.
What is a “data scientist,” and does your organization need one? Can your current personnel of statistical, business, and data analysts perform the duties of a data scientist? Does big data require “data science” to enable the analytics that you need?
This TDWI Webinar will describe what data scientists do, their capabilities, and how they differ from other personnel, including those devoted to business intelligence and data warehousing. This Webinar will help organizations determine whether they need data scientists, particularly for projects involving big data. It will also address the “people issues” involved in gaining analytical value from big data.
You will learn:
- The definition, role, and background of data scientists
- How data science differs from and is similar to data, business, and statistical analysts’ work
- How to integrate data scientists with personnel devoted to BI and data warehousing
- Case studies of data scientists at work