Data sources can come with messy data that is hard to analyze. In this video, learn how to clean up source data.
- [Instructor] When you work as a data analyst, one of the most difficult tasks you will be asked to do is to clean data that comes in from multiple sources. Fortunately, Tableau has some tools that you can use to do that. In this movie, I will show you how to use the data interpreter, which is built into Tableau itself. I have started Tableau and I'm on the main start screen, and I want to connect to an Excel file. So in the Connect task pane, under to a file, I will click Microsoft Excel. And then, in the Chapter02 folder of the exercise files collection, I'll click CleanData.xlsx. And my data appears, but it doesn't look quite right. You can see that I have field number one, products as of February 29, 2020, and then a couple of null values, and then beside that I have ProductID, Product Name, Product Category and null. So it looks like there is something wrong with the initial data source. I've already opened CleanData.xlsx in a separate window, so I will display that now, and it looks like the error is that I have a title or header above the header row of the table, or at least the data list. It's not currently formatted as an Excel table. So I have ProductID, Product Category, Product Name, Product Price, and so on, but I have this line up here at the top that's causing me the problem. The best way to solve this problem would be to delete this line from the original data source. However, if you don't have access to the original data source, such as when you're connecting to a remote file, you can use the data interpreter to try to fix the problem within Tableau. And from here, I can go over to the left side of the screen, and under sheets I will check use data interpreter. And you can see that the data interpreter has eliminated the extraneous title at the top, and as a result we see our correct column headers, ProductID, Product Category, and so on, and all the data looks good and there are no null values that shouldn't be there. If you want more information on what happened, you can click the review the results link and a new Excel workbook appears and you see that it has key for the data interpreter as a worksheet and it indicates what type of changes were made. So if you scroll down, you can get more information about that. And on sheet one, you'll see that there is an indication of what data was cut out. So that's good information if you want to see what was done. In this case however, we can switch back to Tableau and work with our data. So I'll go to sheet 1, and I have product category. So I will drag product category to the rows shelf. And then, number of records. That will indicate the number of products within each category, so I'll drag that to the data area and we can see those values there. The example of data cleaning that I've shown you here is about as simple as they come. And if any of you watching this course who have had to bring in data from multiple sources or one particularly ugly source, know how difficult this can be. If you need to clean source data frequently I recommend looking into Tableau Prep, which is a newer cleaning program that Tableau added in late 2018.
- Explain where a user would navigate to seek specific help in Tableau.
- Determine the best approach for using Excel in Tableau.
- Interpret how to use the features and functions of Tableau when creating charts.
- Describe how best to manage data in a worksheet or visualization.
- Explain how to create a selection filter for certain values.
- Explain how to manage data for different chart formats.
Skill Level Beginner
1. Introducing Tableau
2. Managing Data Sources and Visualizations
3. Managing Tableau Worksheets and Workbooks
4. Creating Custom Calculations and Fields
5. Analyzing Data
6. Sorting and Filtering Tableau Data
7. Defining Groups and Sets
8. Creating and Pivoting Crosstabs
9. Creating Basic Visualizations
10. Formatting Tableau Visualizations
11. Annotating and Formatting Visualizations
12. Mapping Geographic Data
13. Creating Dashboards and Actions
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