What is being data driven? Discover customer analytics and why it’s an important tool. Consider course topics like how to build financial models for finance, investments, and banking.
(upbeat music) - Being data driven or making data based decisions. You've heard about it. People talk about how it's boosted their business, but what exactly does it mean and not only that, but who does it serve? Ultimately, making data a part of your business analysis serves the customer and when you treat the customer well, they'll do the same in return for your business by word of mouth, social media, and even reviews on websites. This type of data analysis is called customer analytics and it's quickly becoming the primary tool set that's needed to support customer experience initiatives. - Predictive analytics does not predict the future. There are too many variables to ever safely know what is going to happen. Rather, predictive analytics attempts to determine which future events are the most likely. Amazon does not know exactly what you buy when you put peanut butter in your cart. However, past behavior from other customers suggests it'll probably be jelly. But, this is by no means a certainty which is why Amazon gives you more than one recommended product. - Rather than asking like, how should you structure your data science team, is ask the question of what does it mean to be data driven? And a data driven organization takes in data fast, quickly processes it in a timely manner, and turns that into efficiencies to navigate the competitive landscape or to build new data products. And once you start with that, then you can ask, well where do I want lift to happen? Where do I want those benefits to happen for that? And that may be within certain teams, they may be broad based. And once you start with that, then you can say, okay, what style of data science team do I? Do I need more of an AI team? Do I need more of a decision sciences team that's helping me think about the choices we're going to make as we navigate the competitive landscape. - [Instructor] I want to show you how to build financial models for use in corporate finance, investments, and banking. We're going to learn how to do financial forecasts in a model to understand where a firm is headed in the future. We're also going to see how we can evaluate financial models to answer important questions for the firm. Finally, we're going to learn how to update our models to make them easier to read, avoid problems like circular references and build in advanced tools like scenario analysis. All of this will be done through the lens of Excel: the key tool in finance. - [Teacher] Compare Group A with Group B to find out if there is a significant difference in their means. Okay, that's a fairly simple task. Now do the same thing with groups A, B, and C. All right, now much more difficult. Now figure out which groups have caused one or more significant differences. Ahh, that requires a lot more thought. I'm going to show you how to use the Tukey HSD and Scheffe multiple comparison tests to run an analysis following an ANOVA. The end results will show you which groups bring about significant mean differences.