Everything You Need to Know About Tableau Reporting

Published: June 9, 2023
Last Updated: September 20, 2023
Chief Strategy Officer at Alpha Serve
Tableau is one of the top reporting tools that help businesses simplify raw data and present it in easily digestible formats. This software lets you generate reports that are accurate, rich in visualizations, and interactive so you easily gain insights from business data.

In this article, we’ll explain all you need to know about Tableau reporting and provide a step-by-step guide and best practices for creating reports in Tableau.
Everything You Need to Know About Tableau Reporting

What is Tableau Reporting

What is Tableau Reporting
Tableau is one of the world’s leading business intelligence software. But what is Tableau reporting? It is the process of extracting information from data and converting it into a detailed, easy-to-understand summary with appealing visuals, graphs, and charts using Tableau.

As a reporting tool, Tableau lets you connect to different sources of business data so you can build data visualizations and dashboards that can be included in your sharable reports.

Is Tableau a Reporting Tool

So is Tableau a reporting tool? The answer to this question is yes. Tableau is indeed a reporting tool, but it's also a comprehensive data visualization and business intelligence platform.

It generates reports but also processes vast amounts of data to provide easy-to-understand, interactive, and dynamic insights. While some confusion arises because Tableau's capabilities extend beyond traditional static reporting tools, its strength lies in its ability to offer fluid, interactive data exploration.

Thus, Tableau is a powerful solution that goes beyond simple reporting to provide sophisticated data analysis and visualization.

Understanding Tableau as a Reporting Tool

Tableau reporting tools let you create interactive dashboards (workbooks) that you can share as reports with other users. Tableau can work with data from one source or blend data from multiple sources to create visualizations. Creating reports in Tableau Desktop or Tableau Online (Tableau Cloud) involves working on a worksheet, which is essentially a blank canvas or editor.

On your worksheet, there’s a 'Data Pan' which displays all the available fields from the data source you have connected to Tableau. Your data fields are organized into 'Dimensions' (categories) and 'Measures' (numerical values) which you add into the 'Rows' and 'Column' sections to create charts and graphs. Fields added into the row sections are displayed vertically on the blank sheet while those added to the column sections are displayed horizontally.

Alternatively, Tableau has a drag-and-drop interface where you can simply drop your data fields to create visual charts. Tableau lets you customize your data visualizations by varying the color, size, and labels. You can also add tooltips and text to each chart to make it even more visually striking and easier to understand.

Tableau enables users to apply filters to their data as part of their analysis or organize their reports into pages based on how they want to present the selected fields. Reporting in Tableau involves creating various types of charts and graphs to visualize data.

Tableau also offers advanced functionalities such as time series, trendlines, and data forecasting. These features make your data reports even more robust because they allow you to forecast and include other forms of predictive analysis on your data.

Benefits of Using Tableau for Reporting

Tableau is highly regarded as a premier tool for creating interactive and informative visualizations and reports that make complex data easy to understand.

The following are some of the benefits of using Tableau vs. other reporting tools:

1 . User-friendly Interface

Tableau prides itself on its intuitive data visualization capabilities, making it accessible to users of varying skill levels. Its simple drag-and-drop functionalities enable even non-technical users to organize their data into compelling visualizations.

2. Flexibility

Tableau's flexibility as a reporting tool extends to its diverse range of visualization options, allowing you to build reports that effectively communicate your data. Furthermore, the ability to add interactivity within individual reports empowers users to change views for different perspectives on the presented data.

3. Handling Big Data

As a robust and reliable tool, Tableau can effectively handle large volumes of data, making it a preferred choice for businesses dealing with big data.

4. Real-time Reporting

Tableau's efficient connectors allow seamless connections to data sources and can transmit data in real time. This ensures your data is always current and reliable, even when updates occur at the source.

Tableau Reporting Tools Overview

Tableau Reporting Tools Overview
Tableau has various reporting tools that help extract and read data from data sources, create informative visualization, and combine these visualizations into an interactive dashboard that users can interact with to learn more about the data being presented. Here’s an overview of these tools.
Tableau Reporting Tools

Data Connection Tools

In every business use case involving Tableau or other analytics tools, data is often sourced from different platforms such as spreadsheets, cloud-based data services like Amazon Web Services, or directly from business applications like Jira or ServiceNow. Users can either import data to Tableau from these sources manually or make use of data connectors to get their data into Tableau.

Tableau has native connectors accessible from the Tableau Desktop platform. There are also partner-built connectors from the Tableau Exchange. The third option is to use a connector built by third-party software development companies such as Alpha Serve.

Third-party Tableau Connectors, like those from Alpha Serve, are plugins that help integrate Tableau with popular software applications. In addition to simplifying the process of exporting data to Tableau, third-party Tableau Connectors also have filters, scheduling options, and other advanced features that make the process of working with large datasets even more seamless.

Find a list of third-party and native Tableau Connectors here.

Data Visualization Tools

Tableau provides a diverse set of visualization options for users to help them uncover patterns, trends, and outliers in their data. The choice of visualization in your reports largely depends on the nature of the data you’re working with and the specific insights you’re aiming to extract.

For instance, if the goal is to show how a variable has changed value over time, then you need to build line charts, slope charts, or highlight tables. Similarly, if you’re trying to show a correlation between data points, scatter plots or heat maps would work better.

As their name suggests, part-to-whole charts, such as pie charts, area charts, stacked bar charts, or treemaps, illustrate the proportion that each part contributes to the whole.

Magnitude charts such as bar charts, histograms, and packed bubble charts are used to show the relative value of two or more items. Combination charts and bullet charts show deviation while distribution charts illustrate how events are clustered around a specific probability.

Interactive Dashboards

One of Tableau's most powerful features is the possibility of creating interactive dashboards that enable users to engage with their visualizations to delve deeper into their reports.

There are various tools or options to add interactivity to the dashboards you create in Tableau. They include:

  • Global filters/Universal filters
  • Dashboard actions
  • Parameters
  • Tooltips

Data Blending & Drill-Down Features

Data blending refers to the possibility of combining data from different sources for in-depth analysis in Tableau. Tableau lets users combine data seamlessly even when they have different structures or formats and display an aggregated view of the data sets.

The data drill-down feature helps when working with multi-dimensional data that contains datasets with different hierarchies. The drill up or down function lets you view data at the lower or higher hierarchy, depending on the information you’re trying to extract. For instance, if a user is examining sales data collected over several years.

Adding a drill-down function makes it possible to examine the sales data for each month within a year. On the other hand, a drill-up function will make it possible to view data at higher hierarchies.

Creating Reports in Tableau: A Step-by-Step Guide

Creating Reports in Tableau: A Step-by-Step Guide
Tableau is appreciated for its simplicity and user-friendly interface, which make it easy to integrate data and create advanced visualizations for reports. Here’s a step-by-step guide on how to create reports using Tableau.

1. Connect to Your Data Source

To start building reports in Tableau, the first step is to connect to a data source. This could be via the inbuilt connector, partner-built connectors, or a third-party plugin like AlphaServe's Connectors for Tableau.

Each connector type has its specific setup process, typically involving the creation of a data source within the application you’re exporting data from, with data filtering as required.

2. Prepare Your Data

The next step is to clean up and prepare your data to ensure its accuracy and relevance for analysis. This involves removing irrelevant or duplicate data, unwanted outliers, structural errors such as typos and incorrect capitalization, and handling missing value data.

Tableau's Data Prep feature can assist in streamlining this process.

3. Create a New Worksheet

In Tableau, a worksheet is a canvas where you create visualizations. To create a new worksheet, use the “New Worksheet” button or the respective keyboard shortcut. Once created, you'll find 'Dimensions' and 'Measures' on the left side of the screen.

4. Build Your Visualization

To create a visualization, drag and drop a 'Dimension' to the 'Rows' or 'Columns' section and a 'Measure' to the 'Marks' section of your worksheet. Then, select the type of chart, map, or graph you want to create. You can customize the size, color, text, and other features of your visualization to increase interactivity.

5. Create a Dashboard

A dashboard is a collection of various visualizations used to create a report. To create a new dashboard, use the “New Dashboard” option in the workbook menu. Once created, add the visualizations from your worksheets to the dashboard by dragging and dropping them.

You can also apply filters or add other interactive elements to your dashboards and utilize the dashboard layout options to organize the visualizations.

6. Share Your Report

Upon completing your dashboard, you can share your report with others. To do this, click on the “Share button” in the toolbar within the workbook you want to share. You’ll receive a direct link to your report, which you can then share.

Alternatively, you can export your report as a PDF, image, or Tableau Workbook or publish it directly to Tableau Public, Tableau Server, or Tableau Online.

Tableau Reporting Examples

Tableau reporting tool is versatile in that it works for various business scenarios. You can use this software to derive data-driven insights from data across sales, marketing, customer service, and other business use cases.

The following are some Tableau reporting examples that you can create with this software:

Sales Commission Model

This report, created in Tableau, displays the relationships between compensation types, commissions, and quota attainments for a sales team. It offers an interactive experience, allowing viewers to adjust variables such as quotas, commission rates, and base salaries.

Additionally, users can sort the results in ascending or descending order or alphabetically by salesperson names.

Measuring Customer Satisfaction

This dashboard visualizes data from a customer satisfaction survey where ratings are given on a scale of 1 to 10.

The report employs a correlation graph to display the relationship between overall customer satisfaction ratings, firm expertise, and the likelihood of customers recommending the service or product.

The view can be filtered based on industry, job function, gender, and product to provide more specific insights.

Profitability and Shipping KPIs

This report consists of two dashboards tracking key performance indicators related to profitability and shipping across multiple companies.

The profitability dashboard tracks which companies generate the most or least profit, while the shipping KPI dashboard monitors shipping delays. The graph uses color coding to facilitate quick performance assessment.

It also includes a chart providing a snapshot of profitability by the company and average delay times, offering a comprehensive understanding of the operational effectiveness of each company.

Tableau Dashboard Best Practices

Creating effective dashboards in Tableau requires adhering to best practices that enhance user experience and ensure clear communication of data insights.

Here are some Tableau dashboard best practices to consider:

1. Choose the right visualizations based on your report's goals and the message you want to convey.

2. Opt for a simple and clean layout that effectively communicates the data without causing clutter or confusion.

3. Incorporate interactive features like filters and highlighters to enhance the user experience and convey multiple pieces of information within a single report.

4. Ensure your dashboard is optimized for quick loading times and seamless operation across various devices and screen sizes.

5. Maintain consistency in the design elements, such as colors, fonts, and shapes, across all your visualizations to create a unified and visually pleasing report.

6. Provide adequate context to your data using labels, annotations, and tooltips to help users better understand the information presented.

7. Always test your dashboard on multiple devices and with different user groups to identify potential issues or areas of improvement before sharing it more widely.

Enhancing Your Reporting in Tableau

Tableau Dashboard Best Practices
Tableau offers several advanced features, in addition to the basic tools and functionalities, that can be particularly beneficial in creating efficient and insightful reports.

Calculated Fields

Tableau's Calculated Fields feature enables users to create new fields from existing data, which can provide additional insights. Users can perform calculations, apply formulas, and establish custom logic to manipulate and transform their data.

The primary aim of this feature is to create new metrics, ratios, or aggregated values that are not readily available in the original data set.


Parameters in Tableau provide an effective way to create interactive and adaptable reports.

These dynamic inputs can be controlled by users to alter the behavior of visualizations and calculations. Parameters can include values such as dates, thresholds, or categories, which can be incorporated into calculations, data filters, and visualizations.

Adjusting these parameters can make reports more interactive, allowing users to explore "what-if" scenarios, compare different data sets, and gain deeper insights.

Level of Detail (LOD) Expressions

LOD Expressions enable users to carry out calculations at different levels of granularity within a dataset. Users can define calculations that are independent of the level of detail in a given visualization.

This functionality allows for a more precise and granular analysis of the data.

Final Words

Tableau stands out as a potent data analysis and reporting tool with its ability to connect with various data sources. This capability allows users to blend and scrutinize data from multiple platforms seamlessly.

The software boasts an array of data visualization features, empowering users to craft visually engaging and highly interactive dashboards. It is not only a valuable tool for expert data analysts but also an intuitive platform for anyone wanting to extract insights from data, create impressive visualizations, and share informative reports.

With Tableau, users at all levels can contribute significantly to the overall understanding and utilization of data.

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