Excel is one of the most widely used solutions for analyzing and visualizing data. It now includes tools that enable the analysis of more data, with improved visualizations and more sophisticated business logics. In this data science course, you will get an introduction to the latest versions of these new tools in Excel 2016 from an expert on the Excel Product Team at Microsoft.
Learn how to import data from different sources, create mashups between data sources, and prepare data for analysis. After preparing the data, find out how business calculations can be expressed using the DAX calculation engine. See how the data can be visualized and shared to the Power BI cloud service, after which it can be used in dashboards, queried using plain English sentences, and even consumed on mobile devices.
Do you feel that the contents of this course is a bit too advanced for you and you need to fill some gaps in your Excel knowledge? Do you need a better understanding of how pivot tables, pivot charts and slicers work together, and help in creating dashboards? If so, check out DAT205x: Introduction to Data Analysis using Excel.
edX offers financial assistance for learners who want to earn Verified Certificates but who may not be able to pay the fee. To apply for financial assistance, enroll in the course, then follow this link to complete an application for assistance.
*Note: *This course will retire at the end of October. Please enroll only if you are able to finish your coursework in time.
Setup the lab environment by installing Office applications. Learn how to perform data analysis in Excel using classic tools, such as pivot tables, pivot charts, and slicers, on data that is already in a worksheet / grid data. Explore an Excel data model, its content, and its structure, using the Power Pivot add-in. Create your first DAX expressions for calculated columns and measures.
Learn about queries (Power Query add-in in Excel 2013 and Excel 2010), and build an Excel data model from a single flat table. Learn how to import multiple tables from a SQL database, and create an Excel data model from the imported data. Create a mash-up between data from text-files and data from a SQL database.
Get the details on how to create measures to calculate for each cell, filter context for calculation, and explore several advanced DAX functions. Find out how to use advanced text query to import data from a formatted Excel report. Perform queries beyond the standard user interface.
Explore ways to create stunning visualizations in Excel. Use the cube functions to perform year-over-year comparisons. Create timelines, hierarchies, and slicers to enhance your visualizations. Learn how Excel can work together with Power BI. Upload an Excel workbook to the Power BI service. Explore the use of Excel on the mobile platform.
Gregory J Hamel ( Life Is Study) completed this course.
Excel for Data Analysis and Visualization is an intermediate level course offered by Microsoft through the edX platform that covers cutting edge techniques for gathering, transforming and viewing data in Excel. The course focuses on getting students...
Excel for Data Analysis and Visualization is an intermediate level course offered by Microsoft through the edX platform that covers cutting edge techniques for gathering, transforming and viewing data in Excel. The course focuses on getting students up to speed with new features and techniques offered in Excel 2016, such as the Excel data model, queries, DAX (a syntax of defining functions) and Power BI, an online productivity service that integrates with Excel. This course assumes you have some familiarity with MS Excel, particularly pivot tables and slicers. You can complete the course with Excel 2010 or 2013, but if you don't have Excel 2016 you'll have to download add ins and you'll have to work slightly harder to complete the assignments. Grading is based on 7 weekly labs and 12 comprehension quizzes.
Weekly content in DAT206x consists of one to three short video lectures describing new Excel features followed by a comprehension quiz. The amount of video content per week is usually under 30 minutes, so you shouldn't need to commit more than an hour or two a week to complete the course. The lecture videos have adequate resolution to see cell values and lecturer's presentation is easy to follow. Weeks 1-7 have lab assignments that let you apply the techniques presented lecture. You only get a couple of submissions for most lab and quiz questions, but most questions are not too difficult.
Excel for Data Analysis and Visualization is a succinct, informative course on new Excel features that is worth checking out for those interested in going beyond the basics. Using Excel 2016 for this course when it launched only a few months before the course debuted may partially be a ploy to convince Excel users to upgrade, but I can't fault Microsoft for teaching with the latest version of their own product and I completed the course with Excel 2010 without much difficulty.
I give Excel for Data Analysis and Visualization 4 out of 5 stars: very good.
Cameron completed this course, spending 2 hours a week on it and found the course difficulty to be medium.
Good course. Definitely a game-changer in terms of Excel. The main focus is on Power Query, Data Models and DAX (new language in Excel). The course is not extremely difficult to take, but some prior Excel usage would be recommended. Great intro to Analysis...
Good course. Definitely a game-changer in terms of Excel. The main focus is on Power Query, Data Models and DAX (new language in Excel). The course is not extremely difficult to take, but some prior Excel usage would be recommended. Great intro to Analysis on Excel.
The course and its content is great, but sometimes the presentation can be lacking. For example there are compatibility issues depending on the version of Excel you are running. They tackle this in the beginning but there are instances where the course gives you a task to complete, then a quiz to take based on the task, then AFTER those two activities, they tell you what to do if you have issues completing the task due to compatibility issues. This should be listed in the beginning of the assignment, not AFTER the assignment has been completed. People who are having issues with compatibility will not make it to that page.
Additionally, some poorly worded questions that leave you scratching your head and scrolling down to the discussion section where you see other students have raised the same concerns.
Overall though, the good outweighs the bad, and the information you learn really breathes new life into Excel from an analysis perspective. Previously, due to size limitations, Excel was just a dumping ground for me after I had aggregated data on a database like SQL Server. Now, thanks to the flexibility that Data Models create, it has much more functionality for me.