![]() ![]() Analysts also need powerful analysis capabilities. midmarket controller, Nov 2022īut while no-code is important, visual builders are only as good as the technology that underpins them. “Data from multiple sources and systems can be easily extracted and manipulated to create meaningful reports and dashboards with minimal training and experience.” - Marc B. “Once the data is in the workbook we can start creating visualizations by just dragging and drop of columns which is very easy and useful and takes very less manual effort.” - Rohit T., enterprise engineer, May 2023 Some reviews note that users can build visualizations this way without much training or effort. Tableau’s drag-and-drop functionality is popular among users who prefer a visual builder to working with code. Overall though, Tableau checks the boxes for connecting data from Excel files, SQL databases, Salesforce, and more and turning around standard charts, graphs, and dashboards. Reviewers do call out shortcomings in the ability to customize visualizations and iterate on the underlying data sources-more on that in a later section. "The data visualization functionality is very powerful and really helps tell the stories behind the data."- Excerpt from Tableau pros & cons “Tableau helps me visualize massive amounts of client data that can then be used to create actionable insights by crunching the data into simple to read visuals that can be understood by anyone.” - Yash G., SMB analyst, May 2023 Reviews like this make it clear that visualizations are a key component of why companies choose and stay with Tableau: Once a data source is connected, anyone can build visualizations (or “vizzes”, as they’ve nicknamed them). The BI solution has quite a few out-of-the-box formatting options and plenty of options to visually present data to stakeholders. Tableau is lauded by users for its easy-to-create charts, graphs, and maps. Learn how Mode compares to Tableau Quick, easy visualizations Other common pros include the ability to connect large data sources, quickly build dashboards, and integrate Tableau into the greater Salesforce ecosystem. Since Tableau’s biggest strength has historically been its visualizations, it’s no surprise this feature shows up frequently in positive Tableau reviews. You can also check out “ What Is Tableau and What Is It Used For?” to learn more about how analysts use the software and " Tableau Pricing: How Much Tableau Costs" to learn about how costs can creep up on data teams using Tableau. ![]() Read on for a showcase of what users say about Tableau pros and cons, their most important use cases, and cost vs benefit of Tableau’s solutions. Since there’s so much to uncover as you consider investing in a new solution for data visualization and exploration, we’ve curated some of the more relevant reviews around Tableau's strengths and weaknesses. For information about how to configure R or Python to use in your flows and how to create your scripts, see Use R (Rserve) scripts in your flow (Link opens in a new window) or Use Python scripts in your flow (Link opens in a new window).If you’re looking for Tableau reviews, sites like G2 and Capterra can feel overwhelming-they have thousands of reviews from users in many roles at businesses of all sizes. If you author or edit flows in Tableau Server (version 2020.4.1 and later) that include script steps, Tableau Server must also have a connection to an Rserve or TabPy server to run script steps. Otherwise, the output will use the fields from the input data. If you want to return different fields than what you input, you'll need to include a getOutputSchema function in your script that defines the output and data types. When you create your script, you will need to include a function that specifies a data frame as an argument of the function. You can continue to apply cleaning operations to the results and generate your output for analysis. Tableau Prep passes the data to Rserve for R or Tableau Python server (TabPy) for Python and returns the resulting data back to the flow in the form of a table. Also, script steps are not yet supported for flows authored or published to Tableau Cloud.Ĭonfigure your Rserve server or Tableau Python (TabPy) server and add a script step to your flow. Note: Connecting to scripts as an input step for your flow is not yet supported. ![]() Data is passed from the flow as input through the R or Python script step, then returned as output data that you can continue cleaning using the features and functions of Tableau Prep Builder. Starting in version 2019.3.1 you can use R and Python scripts to perform more complex cleaning operations or incorporate predictive modeling data into your flow.
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