[MUSIC] In this video we're going to look at the role of Excel in data and analytics. Excel has been around for a long time, and many viewer as the first tool to learn when you're starting out in the data and analytics field. The next two courses in this specialization will go into detail on exactly what Excel can do and how you can use it. In this video, I'm going to talk at a high level on what the tool is, how it's used, and what types of problems it can solve. Excel is a spreadsheet developed by Microsoft. It has calculation, graphics tools, pivot tables, and a macro programming language called Visual Basic for Applications, VBA. Excel lets you organize numeric or text-base data in spreadsheets or workbooks. You can take raw data and organize it and rearrange it, so that you can perform complex analysis of the data. To visualize your data, Excel allows you to create different types of charts, including line and column charts, or add miniature graphs called sparkline. You can also use Excel to apply a table style, create pivot tables, quickly insert totals, and apply conditional formatting. So, why would you use Excel, when there are so many more robust and analytics tool available? Here are some of the key benefits of Excel. It's easy to use. It's extremely versatile. It's dynamic, making it easy to explore "what if?" scenarios. Complex data can be presented in a clear and visually appealing way. It can automate data processing. It integrates with Microsoft Office. And of course, everybody has it. Excel is a very common tool for data and analytics. There are many, many options out there that you'll learn about in this course, but Excel is an excellent one to start with in your career in data and analytics. It can be used to analyze data in many different job types for different reasons, and many of the Excel skills you will learn translate to more advanced tools in the industry. Here's an example of how we used Excel to combine sales data by distribution channel to look at growth opportunities by product and country for a medical device organization. We combined their historical data along with macroeconomic data, and developed models that allowed the company to predict sales based on varying assumptions. These models were also displayed in graphs, and BBA was used to provide a user interface that allows the client to toggle between the views and produce multiple scenarios based on varying assumptions for comparison purposes. In this video, we discussed the role of Excel in data analytics. Excel is an easy to use tool that is extremely versatile. Learning Excel will make it much easier for you to pick up more complex data and analytics tools in the future. [MUSIC]