Quickly create financial forecasts using big data, predictive analytics, and Microsoft Excel.
- [Michael] Hi, I'm Dr. Michael McDonald. I'm a professor of finance and a data science researcher. I've taught big data and financial forecasting to numerous executives at many Fortune 500 companies and government agencies. In this course, I'm going to show you how to use data to effectively forecast key performance indicators in business. Business analytics is one of the fastest growing fields in business, and it is a key area in which firms are looking for talent.
Making forecasts with data is a critical part of the business analytics discipline. In this course, you will explore how to use data to make forecasts based on a statistical technique called regression. We'll explore the steps involved in going from a straight forward business question to a complete forecast for the future. This includes gathering data, cleaning data sets, and performing complex data analysis.
Let's get started.
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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- 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.