Business Intelligence (BI); the term is bandied about so frequently today that it might seem like everyone except you already understands it. The truth is that like its partner “Big Data”, business intelligence is actually not well understood at all. Most people who talk about business intelligence have at best a general notion of what it means and almost no experience with actually using BI in a meaningful way. However, BI is an important new tool for modern business. This course goes in depth on the importance of business intelligence and how to use it for your business, beginning with the fundamentals of business intelligence. The course also covers how to collect, clean, and work with data, the fundamentals of data analysis and how to structure data correctly to apply and use it, as well as how business intelligence can help with pricing strategy and financial forecasting.
Learning Objectives
- Recognize what business intelligence (BI) is and explore how business intelligence works on a theoretical basis
- Identify what steps firms need to take to implement business intelligence and what areas where business intelligence can alter the way a company conducts operations
- Explore how to critically examine databases produced by Business Intelligence (BI) software packages like those from Salesforce, Tableau, Oracle, IBM for issues or concerns
- Recognize how to gather relevant data from publicly available databases
- Explore how to merge datasets together based on unique identifiers to create a single useable database
- Identify and examine data via automated tools and processes to weed out questionable or erroneous data points
- Discover how to evaluate data for accuracy using Benford’s Law
- Explore how to develop ratios and relative metrics to better evaluate data, how to develop moving average and other tools to smooth data over time, how to create binary variables and decile rankings to evaluate data structure, how to run basic univariable analysis of means, medians, and percentiles on a dataset, how to run simple regression analysis on a dataset, how to run instrumental variables analysis on a dataset, how to run probit/logit analysis on a dataset, how to run fixed effects regression on a dataset, and how to run difference-in-differences analysis on a dataset
- Recognize univariate statistics and differences between statistics and the coefficients on regression analysis
- Identify precision of coefficient estimates based on confidence intervals and the driving factors of a business outcome based on statistical significance
- Recognize the differences between statistically and economically significant coefficients
- Explore limitations on specific statistical tests used in business intelligence, the basics of pricing and why it matters for business, and what price discrimination is and how it can be useful to a firm
- Identify different types of price discrimination and their uses
- Explore how to use price discrimination to maximize profits and revenues and how to apply Business Intelligence (BI) techniques to pricing analysis
- Discover how to create a basic set of income statement, cash flow, and balance sheet forecasts and recognize the linkages between different items across the financial statements
- Identify how changes in growth assumptions impact financial forecasts and explore the use of regression analysis to determine forecast growth rates using outside variables (e.g., GDP and inflation)
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Prerequisites
No Advanced Preparation or Prerequisites are needed for this course.
However, basic understanding of concepts in statistics is helpful but not required – mean, median, standard deviation, and what data is for instance.