The Tableau Prep Interface and the Input Step
Welcome back to the articles on Tableau Prep. Today we’ll be discussing the interface of Tableau, how to use it, and the Input step In Tableau.
The Start Screen and Connecting to Data
When we open Tableau, we begin on the start screen. At the far right, we have the discover pane, which shows education resources and links to relevant content. In the middle, we are shown previously opened files, and to the left, we have the connections pane. We will open a file in the way described in the previous article.
The Input Step
We will select a data file from the connections manager and drag out a table. This creates the first step in the flow and Input step. There can be multiple input steps, and whenever you click on one, the related input pane will be brought up.
In the Input pane, you can select which rows you want in your flow, and how you want to sample your data from the ‘Data Sample’ tab.
From the ‘Multiple Files’ tab, you can add filters to the rows by clicking the ‘filter values’ option. Upon clicking, you will be shown a calculations screen, where you can add the filters.
If you want to remove the filter, right-click the filter option in the table and select ‘remove’.
To use a new connection, simply click the plus sign on the right beside connections, select your file type and then select the sheet you want to use and drag it to the flow pane as well.
In case of multiple sets of data, select ‘Wildcard union’. (You will have to select Wildcard Union for every sheet.)
To add another step, we can click the plus sign. We have a multitude of options to select from, a cleaning step, an aggregate, pivot, join, union, and an output.
A cleaning step shows up as a simple bar on the flow pane. Below, we have the profile page, which shows different cards for each column in the data. Each card displays the value in that column and the number of rows for each value. For more information, check out the article on the Profile Pane and Pivot Step.
The cleaning operations are shown in the menu on the individual cards or the contextual toolbar.
We can also perform cleaning operations by direct interaction, such as changing the data type or renaming the field.
Each type of cleaning step we perform will be shown above the cleaning step icon and will be tracked in the changes to the left.
For more information on the cleaning step, check out the article on The Cleaning Step and Group and Replace.
Types of Steps
Here, we have opened a more complex flow. This flow can be broken down into digestible parts. There are a series of pivots that restructure January’s bestseller data, bringing it all together with joins.
There’s a union that combines several weeks’ worth of data for February.
March is also pivoted, and all three months are combined with a union.
Another data source is brought in, which brings with it sales information and aggregates it from transactional data to book-level data, then joins it with bestsellers.
Finally, movie adaptation data is also brought in via another join, and an output is generated for fully cleaned and combined data.
We can click on a step to bring up the pane related to that step. First, let’s start with a pivot step, shown by the ‘columns to rows’ icon.
Fields are brought in from the left side’s list of field to the Pivot Values Drop area. The results, that is, the pivoted fields, are shown on the right, with a profile pane view and a data grid view. For more information on the Pivot step, read the article on the Profile Pane and Pivot Step.
Next, let’s check out an aggregation step, which is indicated by the sigma symbol. Once again, fields are shown on the left and brought either to the grouped fields’ area or the aggregated fields’ area. For more information on the aggregation step, check out the article on the Aggregate Step and the Join Step.
Joining and Unioning
Combining data can be done by either joining data or unioning it. Let’s look at a union step.
A union shows the inputs going in on the left, and on the right, we are shown the profile pane view and data grid view of the results. Each field’s card displays a colored bar, showing which inputs went into that field. There’s also a Table Names column, generated by Tableau, which shows which data source each row came from.
Another way to combine data is joining.
The join step pane provides a visual interface for configuring the join. To the left, we can build a join clause or clauses, choosing which field to join and how.
We can select the join type by clicking on the diagram, and under the join, we can see the summary of results, showing what has been included in the join and what has been excluded.
Immediately to the right of the join configuration pane, we can see a breakdown of join clauses. Values in black are matched and the ones in red are unmatched. Further to the right, we see the profile pane view and the data grid view. For more information on Joining, take a look at the article on the Aggregate step and the Join step.
Finally, once the data has been cleaned and prepped, we must create an output step. Saving the flow as it is will create a .tfl file, not generate an output of the data. A packaged flow file includes the flow and extracts of the flat files, though not the files from the connections. To use the file, an output step must be created and the flow must be run.
In the output step pane, the right side shows a data grid view of what the end result will be once you run the file. The left side allows you to configure the way you want to save your file. It can either be saved to a file or published as a data source. The file can be named and saved as a .hyper extract, .tde extract, or .csv file.
Clicking Run Flow will execute the flow and generate an output file or publish the data source. Note that if a flow has multiple outputs, they can either be run separately or simultaneously. For more information on the Output step, read the article on the Union step and the Output step.
Thank you for reading this article, and we hope you learned some more basics of Tableau.