Data-Driven Decision Making and Analysis Course

An introduction on how to use big data to make better decisions

Half-Day Seminar

(30)

Credits – 

CEU: 0.3  

A report is sitting on your desk, another is waiting in your inbox … now what? According to Forbes, "Now more than ever data, analytics and expertise will experience an ascendancy, will come into vogue, will become as omnipresent as a weather forecase or baseball score, will reflect an emergence from the superstition of the Dark ages into light." More bluntly put, "Ignore the data at your peril." Join this 3-hour online interactive learning session where you'll gain the skills to transform big data into better decisions.

Numbers drive every major business decision. Reports, Excel spreadsheets and extrapolated data are only a click away; however, without knowledge, a data set is just a series of numbers with no meaningful contribution before being analyzed. As individuals we need to be able to take that data and utilize it to make informed decisions that produce the best, real-world results.

But which numbers matter? Should we focus on numbers or percentages? Are we even reading the data correctly? Are we on track for success or failure? And perhaps that biggest question, "Where do we begin?" Join this information-packed half-day seminar to learn the answers to all these questions and more. Get comfortable making important decisions with big data.

Data-Driven Decision Making and Analysis Course 

An introduction on how to use big data to make better decisions

Numbers drive every major business decision. Reports, Excel spreadsheets and extrapolated data are only a click away; however, without knowledge, a data set is just a series of numbers with no meaningful contribution before being analyzed.

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  • The Roadmap from Data to Results.
  • A 3-Dimensional approach to analysis.
  • The questions you want the data to answer.
  • Calculate trending with any timeline.
  • Linear (straight line) vs. Non-Linear (seasonal or surging) trending.
  • Adjusting your analysis for facts that you know the data isn’t stating.
  • Demonstrating why averaging isn’t good enough.
  • Numbers vs. Percentages: is one better than the other?
  • Effective ways to present data.
  • Analyzing and interpreting big data sets for others.
  • Employing recommended tools to automate Repetitive Analysis.
  • And more.

Management, Finance, Human Resources, Purchasing/Inventory Control, Sales and others relying on reporting/data to find better ways to spot opportunities to improve results.

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