Join Michael McDonald for an in-depth discussion in this video Wrap up, part of Financial Forecasting with Big Data.
- [Michael] In this course, we've talked about what business intelligence is, and the role that it plays in business analytics. We've explained how to use regression analysis to make forecasts of key performance indicators based on hard data. We've outlined the steps involved in a business forecasting project, from choosing a question to gathering data, to running a regression, to stress-testing our results. And, we've performed several examples of real-world business forecasting based on actual data from companies just like yours.
Remember, business analytics is complex and making forecasts is one of the most challenging parts of the discipline. So what can you do from here? Well, I urge you to keep developing your skills. Think about how you can apply regression analysis to key questions you see in your day-to-day role. Look for opportunities to put data to use in new ways. Keep an eye out for ways to answer questions with data that others might not have thought of.
And of course, look for future courses in this subject right here in the library. Thank you for watching, I wish you all the best in your career.
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.
- 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