![]() I'm using Tableau 10.5 still, so perhaps there is an easier way to do this is in the latest version of the software, but my issue was that I have 4 csv files of data in one network location and a separate csv file in a different network location that I want to union together. Not that data blending doesn't work, but it can be difficult for non-IT users to understand the level at which their data is being linked. Previously, if you wanted to use multiple data connections, they were separate and your only option to bring them together was data blending (unless you wanted to put the data in the same location on the back end) I try to avoid data blending at all costs. I particularly like the ability to union csv files, pivot your data, and creating multiple connections to be used in a single data source. ![]() This section will show you how to clean data on a column level.Tableau has made a lot of progress in regards to preparing your data and I'm not even including Tableau Prep in that statement. As a consequence, you will have to sort out the mess before you can get reliable results from an analysis or a dashboard. Don’t blindly trust these recommendations, but they can point out data flaws you might have missed otherwise.ĭata is often messy, involving null values, typos from manual entries, different formatting, changes in another system, and so on. My way of working would be, look at the recommendations, check if they make sense, and execute the change-or not. ![]() This feature can be useful, especially for unfamiliar datasets. This is probably the case because the column does not contain any data or contains only a small amount of data. ![]() The second, third, and several more recommendations after listing_url are to remove certain columns. The column listing_url for example is being recognized as a webpage and therefore Prep recommends you change it to the data role URL. Tableau Prep Builder analyzes the column content and proposes changes that might fit the data. Also note the recommendations Tableau Prep Builder gives you: During the cleaning step, multiple operations can be performed, such as filtering or creating a calculated field. To create the cleaning step, the user can simply click on + next to the input and select Add: Clean Step. We have seen the following canvas before in the The Tableau Prep Builder GUI section. In this article we will take up Cleaning Data. We will divide the prepping features into five subcategories: cleaning, unions and joins, aggregating, pivoting, and scripting. I hope that by the end of this chapter you will be able to cut your time spent data prepping in half (at least). Sometimes I even use it for datasets I don’t want to visualize in Tableau Desktop, just to get a quick overview of, for example, how many rows contain a specific word, how many columns are needed, what happens to the date range if I filter a particular value, and so on! Within a few minutes I have insights that would have taken me much more time to get with database queries or Excel functions. To me, the best part about Tableau Prep Builder is that it can handle a huge amount of data. Fewer queries in Tableau Desktop means faster generation of dashboards. The fact is, the closer your Prep output data is to what you need for your Tableau Desktop visualization, the more efficiently VizQL will run on Tableau Desktop. It really depends on the dataset itself and the expected output. Other times you might just run an aggregation (one feature) and be done. Sometimes you might use many different tools to prepare your dataset in order to get it in the shape you desire. Tableau Prep Builder comes with lots of distinctive features. Next, we will continue by adding more data sources. The lower pane will always show the data source of the selection made at the row level. So far, we have seen that, after loading data in Prep, visual filters can be applied by clicking on a field or bar in one of the columns. Once you have selected the input data needed, click on the + in the flow pane and select Add: Clean Step. The data type options are, for example, strings, dates, or numbers. In the input pane samples (the section marked with D) you can select and deselect the fields you want to import and change their data types. Also, you can limit the sample set that Tableau Prep Builder will print to increase performance. In the input pane (the section marked with C) you can use the wildcard union (multiple files) function to add multiple files from the same directory. D: The input pane samples, showing the fields you moved to the connection pane, including sample values.C: The input pane settings, which give you several options to configure your input.B: The flow pane, which shows your current Prep flow.A: The connection pane, showing you the input files available at the location selected.
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