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Data Is The New Science And

What Is A Data Scientist?

Data Scientists Are Big Data Wranglers, Gathering And Analyzing Large Sets Of Structured And Unstructured Data. A Data Scientist’s Role Combines Computer Science, Statistics, And Mathematics. They Analyze, Process, And Model Data Then Interpret The Results To Create Actionable Plans For Companies And Other Organizations.


Data Scientists Are Analytical Experts Who Utilize Their Technology And Social Science Skills To Find Trends And Manage Data. They Use Industry Knowledge, Contextual Understanding, Skepticism Of Existing Assumptions – To Uncover Solutions To Business Challenges.


Data Science Is A "concept To Unify Statistics, Data Analysis, Informatics, And Their Related Methods" To "understand And Analyze Actual Phenomena" With Data. It Uses Techniques And Theories Drawn From Many Fields Within The Context Of Mathematics, Statistics, Computer Science, Information Science, And Domain Knowledge.


In Business, Data Scientists Typically Work In Teams To Mine Big Data For Information That Can Be Used To Predict Customer Behavior And Identify New Revenue Opportunities. In Many Organizations, Data Scientists Are Also Responsible For Setting Best Practices For Collecting Data, Using Analysis Tools, And Interpreting Data. 


Where Did They Come From?

Many Data Scientists Began Their Careers As Statisticians Or Data Analysts. But As Big Data (and Big Data Storage And Processing Technologies Such As Hadoop) Began To Grow And Evolve, Those Roles Evolved As Well. Data Is No Longer Just An Afterthought For IT To Handle. It’s Key Information That Requires Analysis, Creative Curiosity, And A Knack For Translating High-tech Ideas Into New Ways To Turn A Profit.


The Data Scientist Role Also Has Academic Origins. A Few Years Ago, Universities Began To Recognize That Employers Wanted People Who Were Programmers And Team Players. Professors Tweaked Their Classes To Accommodate This – And Some Programs, Such As The Institute For Advanced Analytics At North Carolina State University, Prepared To Churn Out The Next Generation Of Data Scientists. There Are Now More Than 60 Similar Programs In Universities Around The Country.


What’s In A Data Scientist’s Toolbox?

Data Visualization: The Presentation Of Data In A Pictorial Or Graphical Format So It Can Be Easily Analyzed.


Machine Learning: A Branch Of Artificial Intelligence Based On Mathematical Algorithms And Automation.


Deep Learning: An Area Of Machine Learning Research That Uses Data To Model Complex Abstractions.


Pattern Recognition: Technology That Recognizes Patterns In Data (often Used Interchangeably With Machine Learning).


Data Preparation: The Process Of Converting Raw Data Into Another Format So It Can Be More Easily Consumed.


Text Analytics: The Process Of Examining Unstructured Data To Glean Key Business Insights.




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