![]() In normal circumstances, to get an average, we would have to create a formula to add each row and divide by the total number of rows. We realize there are over 100 items that would need to be calculated. ![]() Let’s say we wanted to get an average of company revenue for the month of June. Functions in Excel are organized by several categories, including mathematical, statistical, logical, financial, and date and time-based. Becoming familiar with all of the tools to analyze data can seem daunting, but one key benefit of using a spreadsheet is the ability to use functions. By filtering our data, we are now able to only see the rows that meet the filter criteria and it allows us to better analyze our information. By adding a filter, we can now choose to only see items with a ‘MONTH_ID” that is equal to “11”. We now decide that we only want to see the data for the month of November. After sorting and removing the duplicate row, we find that the view needs to be more specific to meet our requirements. For example, if we wanted to check for duplicate order numbers, we could sort the data and quickly see any duplicates. By sorting the data, we are able to organize it based on conditions such as alphabetically or numerically. The most basic step would be to filter and sort the data. How big is the dataset? What type of filtering is required to find the necessary information? How should the data be sorted? What type of calculations are needed? Now that we have visualized the final output, we must decide the best approach to shape our data. Below are some questions to ask before beginning the task. Before we make any changes or adjustments, we will need to visualize the final output. Deciding how to manipulate our data can sometimes be difficult. ![]() In this video, we will discuss the importance of filtering, sorting, performing calculations, and shaping our data to provide meaningful information. Now that we have learned how to collect and clean our data, it is time to decide the best method for analysis. You'll have worked with multiple data sets and spreadsheets, and will have the skills and knowledge needed to effectively clean and analyze data without having to learn any code. The final project will allow you to showcase your newly acquired data analysis skills by working with real data sets and spreadsheets.īy the end of this course, you'll have a solid foundation in using Excel for data analysis. You'll learn how to clean and format your data efficiently, and convert it into a pivot table to make it more organized and readable. With each lab, you'll have the opportunity to manipulate data and gain hands-on experience using Excel. There is a strong focus on practice and applied learning in this course. From there, you'll learn how to perform basic data wrangling and cleansing tasks using functions, and expand your knowledge of data analysis through the use of filtering, sorting, and pivot tables. We'll start by introducing you to spreadsheets like Microsoft Excel and Google Sheets, and show you how to load data from multiple formats. Throughout this course, you'll gain valuable experience working with data sets and spreadsheets. ![]() If you have a desktop version of Excel, you can also easily follow along with the course. No prior experience with spreadsheets or coding is required - all you need is a device with a modern web browser and the ability to create a Microsoft account to access Excel online at no cost. This course is suitable for those who are interested in pursuing a career in data analysis or data science, as well as anyone looking to use Excel for data analysis in their own domain. This course is designed to give you a basic working knowledge of Excel and how to use it for analyzing data. Spreadsheet tools like Excel are an essential tool for working with data - whether for data analytics, business, marketing, or research.
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