In this video, the instructor helps you find questions to be answered with data.
- [Instructor] Business intelligence is useful…for making a wide variety of forecasts,…and helping businesses to be more efficient…in running their operations.…But not all questions can be answered by data realistically.…Some questions are inherently subjective…and don't require data to come up with an answer.…Democrat or republican?…Red Sox or Yankees?…What color is best?…Where should we live?…These are questions that are inherently based on…subjective opinions and there's no data that we can gather…that could help us to make a decision.…
But even when we have questions…that could be answered objectively in theory,…sometimes we don't have data available…or we don't have the right kind of data.…We refer to this as omitted variables bias.…In particular, if we think about questions…on forecasting sales for example,…if we're in a totally new environment…and we've never seen any environment like this before,…it's very difficult to gather data.…If our company has expanded internationally…for the first time selling a completely new product,…
Join Professor Michael McDonald and discover how to use predictive analytics to forecast key performance indicators of interest, such as quarterly sales, projected cash flow, or even optimized product pricing. All you need is Microsoft Excel. Michael uses the built-in formulas, functions, and calculations to perform regression analysis, calculate confidence intervals, and stress test your results. You'll walk away from the course able to immediately begin creating forecasts for your own business needs.
LinkedIn Learning (Lynda.com) is a PMI Registered Education Provider. This course qualifies for professional development units (PDUs). To view the activity and PDU details for this course, click here.
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- Understanding big data and predictive analytics
- Gathering financial data
- Cleaning up your data
- Calculating key financial metrics
- Using regression analysis for business-specific forecasts
- Performing scenario analysis
- Calculating confidence intervals
- Stress testing