Financial Forecasting with Analytics Essential Training
1h 35mIntermediate2021-09-22
Authors
Michael McDonald
Researcher and Professor of Finance at Fairfield University
Course details
Big data is transforming the world of business. Yet many people don't understand what big data and business intelligence are, or how to use that data to evaluate key metrics for their firm in the future. This course addresses that knowledge gap, giving business people practical methods to create financial forecasts with business analytics and big data.
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.
Learning objectives
List the two methods of making decisions.
Identify the most common method of conventional financial forecasting.
Describe common challenges that come when trying to merge data.
Assess the types of questions that business intelligence is best suited to answer.
Distinguish the statistic that is most useful for estimating the impact of an X variable on a Y variable.
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.
Learning objectives
List the two methods of making decisions.
Identify the most common method of conventional financial forecasting.
Describe common challenges that come when trying to merge data.
Assess the types of questions that business intelligence is best suited to answer.
Distinguish the statistic that is most useful for estimating the impact of an X variable on a Y variable.
Skills covered
Corporate FinanceBusiness AnalyticsMicrosoft ExcelFinance and AccountingEssential TrainingData ScienceMicrosoft
Concepts
0. Introduction
- 01 - The role that analytics plays in financial forecasting
1. The Basics
- 02 - What is analytics
- 03 - Business intelligence and company financials
- 04 - Conventional financial forecasting
- 05 - Basics of financial regression analysis
- 06 - Predict values with regression analysis
- 07 - Doing a forecast in Excel
2. Financial Metrics
- 08 - Financial forecasting applications
- 09 - Using data in Excel
- 10 - Decision-making with data
3. Forecasting in Finance
- 11 - Decide on a finance question
- 12 - Gather financial data
- 13 - Clean financial data
4. Performing Forecasting
- 14 - Applied forecasting with data
- 15 - Regressions for forecasting
- 16 - Using Excel for regressions
5. Interpret Forecast Results
- 17 - What do the results mean
- 18 - Confidence intervals around the result
- 19 - Stress testing the results
Conclusion
- 20 - Continuing your financial forecasting learning path