Tableau is a Data Visualization and Analytics platform focusing on Business Intelligence. It lets you connect to data from different sources (can be excel sheets or cloud databases), for analysis, and visualization. Tableau includes several products like Tableau Desktop, Tableau Server, Tableau Mobile, etc. One such product is Tableau Prep Builder which allows you a platform for preparing your data. You can rely on its various services such as Data Combining, Cleaning, and Sharing before analyzing your data Tableau. All the steps taken for preparing data constitute a Tableau Flow.
This article will introduce you to Tableau Workflow and explain the step-by-step method to set up this workflow for your business. It will also dive into an example showcasing the usage of a Tableau Workflow. Read along to learn the steps for creating, managing, and automating your Data Analytics using Tableau.
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What is Tableau Workflow?
The Tableau Workflow is an analytical tool that allows individuals to generate actionable insights from data and share them with other business teams. The current workforce is drawn towards this tool because of its accuracy and security in terms of the data on which you are building your output results.
In any organization, such a workflow requires the involvement of IT, business, and Analytical Teams which can drive its implementation further. Tableau Workflows cater to the need of all these teams and provide a seamless way to analyze data and share your findings. The Tableau Workflow is made up of the following 5 key actions which collaborate together to support your Data Management:
- Access & View
- Share & Govern
To learn more about Tableau Workflows, visit here.
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Steps to Set Up Tableau Workflow
You can easily set up Tableau Workflows for your business using the following 3 steps:
Step 1: Initialize Prep Builder in Workflow
The following image shows what the first screen on Tableau Prep Builder looks like:
As you can see, there are sample flows available to you that you can use for reference. You can also open an existing flow, and use either the sample data or connect data to start a new flow. If you are on Tableau Server, you can click on New -> Flow on the Home page to get started.
Step 2: Manage Your Data in Workflow
For data, if you have an existing data source (MySQL, PostgreSQL, Databricks, etc.), then you can download the corresponding connector and then link the source. You can also upload static files (like Excel, PDF, etc.) and also fetch data from the Tableau Server. We’ll use the sample Superstore dataset available on Tableau Online.
After connecting your data, you can monitor the flow creation on your screen. Moreover, you can also check the various fields that contain your data in Tableau. This will help you in your data cleaning and preparation.
Step 3: Add Steps to the Workflow Task
Once the first step is created, the next task is to add more steps. There are several flow steps available. You can click on the + icon next to the first step to access the various options.
You can now add the following steps to your task:
- Clean Step: This includes a variety of cleaning operations that you can think of, including removal of fields, renaming fields, converting dates, creating calculated values, and so on.
- New Rows: This step allows you to fill gaps in your sequential data. Suppose you have data for the sale on each day of the month, except for public holidays. For analysis, you may need rows for the missing days as well. This step helps you here.
- Aggregate: As you can expect, this step helps create aggregates, like SUM, MAX, MIN, AVG, etc., and allows the grouping of data based on some categorical fields.
- Pivot: Pivoting helps convert rows to columns and vice versa. If you are familiar with pivot tables in Excel, then you shall feel at home with this step.
- Join: As the name suggests, it allows you to join data and combine tables. Those familiar with SQL joins should find the Tableau join step to be familiar. You need to define the left and right keys on which you are joining data, and also the type of the join (left, right, inner, etc.). If your data contains relational database tables, you can even join your data in the input step.
- Union: Union, again, is similar to SQL Union, i.e., combining data by appending the rows of one table to another.
- Script: If you need to write a custom R or Python script for manipulating your data, you can do so with the help of the Scripts step. Note that the scripts can’t be used as an input step to a flow, and script steps are not supported by flows authored/published to Tableau Online.
- Prediction: You can use Einstein Discovery-powered models to predict outcomes based on your data. However, to use this step, you need a Salesforce license and a user account configured to access Einstein Discovery. Once integrated, you can select your prediction definition (like Customer Retention, or Attrition) from a list of options, select predictors, and then map your flow fields to the model fields to run the predictions.
- Output: This step is used to save the output of your flow to a .csv or a .hyper file, or write the output to a database. You can also publish the output as a data source on the server. Note that saving the output to a file is not supported on the web.
- Insert Flow: Use this option to add flow steps from an existing flow to the current flow.
That’s it! Your Tableau Workflow setup is ready. You can understand more about its utility by going through a detailed Workflow example in the next section.
Example of a Tableau Workflow
This section will walk you through the sample superstore flow that is available as a part of the Tableau Prep installation. The flow will be present on your screen and will contain data from 4 geographies (USCA, APAC, EMEA, LATAM) is cleaned (all going through different clean-up operations) and combined using a UNION operation to get the ‘All orders’ data.
This ‘All Orders’ data is further combined with a cleaned Returns data using a JOIN operation, and the resulting data is cleaned and the first output ‘Superstore Sales.hyper’ is created. In parallel, an aggregate operation is performed on the combined data to get the ‘Roll up Sales’. This is inner joined with the pivoted Quota table to generate the second output ‘Annual Regional Performance.hyper’.
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On each ‘Clean’ operation you can access the details of all the listed sub-operations by simply clicking on their icons. For example, on the USCA data, the clean operation filters out the null order IDs, and creates a new field called ‘Sales Region’ with a value equal to ‘USCA’. This is shown in the below image.
You are similarly encouraged to click on each step to understand the operations that take place.
Automating Tableau Workflows
Once a Tableau Workflow is created, you may want to run it at different intervals to see the output as the data changes. You may even like to set up a cron job for executing the flow at fixed intervals, or else run the flow on an ad hoc basis. Luckily, now Tableau allows for flow automation, thanks to Tableau Prep Conductor. The automation setup requires you to manage the following 2 aspects of a Tableau Workflow:
Once your Tableau Workflow is created, navigate to the flow from the Explore Tab, and then click on ‘Scheduled Tasks’. Then click on ‘New Task’ as shown below.
You can then select the schedule for running the task, and select the outputs you want to include as shown in the below image.
Note: If you try to create a Scheduled Task on Tableau Online, you will first have to define outputs for the flow.
If you are using Tableau Online, then, unfortunately, you cannot create a new custom schedule and will have to make do with the available options. However, if you are on Tableau Server, follow the steps here to define your custom schedule.
If your Tableau Workflow execution is dependent on other tasks in your backend, you may need to trigger the execution on an ad hoc basis, and running the Tableau Workflow at a fixed schedule will not be helpful. In this case, you can use the REST API to run the Tableau Workflow whenever required. The detailed documentation of the REST API for running a Tableau Workflow can be found here.
Please note that you either need to be the owner of the Workflow, or a server administrator, site administrator, or project leader with the flow within your scope to run it. If you are none of the above, you need explicit permissions from an administrator, leader, or owner to run the flow.
In this article, you got a broad overview of Tableau Prep Builder and Prep Conductor. Moreover, you understood how to build flows using the steps provided by Prep Builder, and how to automate them using Prep Conductor. This article also links to all the relevant references for further reading at appropriate places. Furthermore, it discussed the 2 key aspects required for implementing Tableau Workflow automation.
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Share your understanding of Tableau Workflow in the comments below!