Since the advent of data analytics, organizations around the world have used it to crunch huge amounts of data, analyze and extract some valuable information out of it. These companies use advanced tools like Tableau to perform complex calculations, visualizations and share the data with other users to create value-driven solutions.
Tableau has numerous features that enable you to add more functionalities and make your reports/dashboards informative and easy to grasp. You can leverage such features and create a multiple KPI tableau dashboard that explains all the necessary metrics and help the stakeholders take real-time decisions.
So, let’s go through the topics that will be covered in this blog on building a KPI dashboard:
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Introduction to Tableau
Tableau is a Business Intelligence and visual analytics platform that equips the user with the tools and techniques to perform data analysis and visualizations by collecting raw information from varied sources.
Tableau supports numerous data sources from where the user can collect and transform it to reveal the hidden insights and relationships between different data variables. This helps you find new leads and learn more about the factors in the market that affect your business.
The visual dashboards in the tableau connected to live data sources provide real-time analysis. It plays an important role in the areas where a business has to make quick decisions based on the current scenarios or measure the performance of its ad campaigns, project team, and more.
Key Features of Tableau
Following are the key features that make tableau one of the best data analytics tools in the world:
The intuitive dashboards in tableau provide a wholesome idea about your data through means of visualizations, text, KPIs, etc. You can also create multiple views and use different types of filters to see only the niche information. You can even copy the properties or visualizations from one dashboard to another dashboard or workbook pretty easily.
With Tableau Server, you can share the dashboards with other users and collaboratively work from anywhere in the world. You can also share both On-premises and hybrid data on the Server and invite other users to mold it as per the requirements.
There are more than 200 data connectors in Tableau Desktop and server that allow you to connect datasets from almost any data source or format. You can add data from Microsoft Excel, RDBMS, MySQL Server, data warehouse, Cloud Servers, JSON, Oracle, etc.
Tableau is also used for data modeling and forecasting. These features give you the capability to assess the current trends in forecasting it, using historical data charts and other visuals.
Security is a major issue in the present data-centric environment. Tableau has a robust surety system that’s based on a series of authentication mechanisms and permissions. Also, you can restrict the amount of data/information a user can access on the server.
Tableau enables the user to connect live data sources with the dashboards and observe the performance of their assets in real-time. This feature is readily used by industries like aviation, marketing, etc.
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What is KPI in Tableau?
Key Performance Indicators or KPIs, in general, are the metrics and values that show how well an organization is performing based on its key business objectives.
We can divide these KPIs into two different categories, high level, and low level. High-level KPIs focus on the overall growth and performance of the company, while low-level KPIs are focused on the workflow or process of each department such as development, sales, HR, marketing, operations, etc.
Now, the tableau KPI dashboard is a collection of multiple indicators that shows an overall image of the current performance through live data connections and visualization techniques.
These metrics could be in the form of charts, graphs, maps, and even tables. KPI’s are generally color-coded or have the shades to represent which makes them more intuitive and understandable.
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Before starting with Tableau KPI dashboards and KPI charts, make sure you have all the resources mentioned below:
- A laptop/computer with a minimum of 2GB of RAM and 1.5GB of free desk space.
- Basic understanding of data science concepts like analytics and visualization.
- Tableau Desktop subscription. If you’re a student, you can create a student account using your institute ID and get the tableau desktop free for 2 years.
- Access to the tableau sample-superstore dataset, you can download from here.
Check out this Tableau tutorial for a step-by-step guide on how to install a tableau desktop on your device.
Now that you know about the KPIs of Tableau, let’s move forward and build the KPI charts in Tableau Desktop and use them in a Tableau KPI dashboard.
How to create a Tableau KPI Dashboard?
To create a KPI dashboard in tableau, you first have to prepare the dataset and transform it into the desired format. Then comes the visualization part that converts the dataset into figures like charts, histograms, maps, scatter plots, and more.
Following that, you apply some filters, create measures and bullet charts to provide more information using a single figure.
At last, put all the KPIs in a single dashboard and share it with other users on the Tableau server. So, let’s go through steps and create a KPI dashboard in tableau:
- Data preparation refers to the process of collecting data from different sources and transforming it into a workable dataset. As discussed above, tableau has more than 200 connectors that allow you to collect data from multiple sources in both structured and unstructured formats. Below are the steps to collect the data and transform it into the desired format: Open the Tableau Desktop and select the data type you want to connect with. Here, we’ll add the superstore datasets which you have downloaded earlier. If not, click here and download it.
- Locate the folder in your disk storage and import the dataset to the desktop. The interface will look like this.
- Now, let’s create some visualizations and charts using the sample superstore data. Select the order ID and Order date and create an area chart for the order count.
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The next step is to convert the datasets into visualizations like tables, charts, graphs, and maps.
- From the bottom-left corner right-click and add a new worksheet. Then, select the sales and Segment variables and create a stacked bar chart by choosing the bar from the top-right corner. Add the sub-category to the Marks sections to separate the bars.
- In this visualization, the categories we’ve added are mentioned in different colors. However, you can change the colors and change them to different shades of a single color. For that, select the Color section from the Marks section, click on Edit colors.
- Now, select the color of your choice from the Color Palette menu and change the color of each Data Item. Apply the changes and add a new worksheet from the bottom-left corner.
- From the Data panel, right-click on the Profit variable, select Create>> Bins.
- Create a Horizontal bars visualization using the newly created field “Profit(bin)” and the SUM(Sales).
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Creating the Key Performance Indicators(KPIs)
Tableau KPIs are created using the calculated field as they show you the values that can tell a lot about your business performance. So, follow the steps below to create the KPIs in tableau:
- Add a worksheet, name it as KPI1 or anything else, click on the dropdown button from the Data panel and select Create calculated Field.
- Rename the KPI and write the formula you want to apply. For example, this KPI calculates the average time taken for an order to deliver.
- Now, drag the calculated field from the Data panel to the Markssection and a value will be displayed on the interface.
- Following that, you can format the KPI layout from the text field of the marks section. Now, click on the three little dots on the right side of the Text option and change the format.
- Apply all the changes and they will be reflected in the interface. You can also change the alignment of your KPI from the same text field.
- In the same way, you can make the Calculated Fields for other KPIs. For example, you can create a benchmark graph that color-separates the sales crossing or underlying a benchmark.
- Apply the formula and other changes and a KPI for sales figures with colored benchmarks will be created.
- Similarly, other KPIs can be added based on your requirements and the type of dashboard you want to build.
Now, let’s move on to the final step, which is to put all the KPIs together on a single dashboard so that it’s easier to share and interact with.
Putting all together in tableau KPI Dashboard
Let’s put all of the above visualizations, calculated fields, and KPIs together and create an interactive KPI dashboard. We’ll create a basic dashboard with two vertical objects and three horizontal ones. However, you can create a completely new dashboard as per your choice. So, follow the step-by-step process mentioned below for creating a KPI dashboard:
- Right-click on the worksheet area and click the New Dashboard button.
- A new dashboard interface with the standard height and width will be created. Drag the Vertical component from the Objects section and drop it on the top of your dashboard layout.
- Following that, click on the Show dashboard title checkbox and change the format of your Dashboard Title.
- Now, repeat the first process of adding more vertical and horizontal objects as per your requirements and start dragging the visualizations from the sheets section on the Dashboard panel.
- You can add more visualizations by simply changing the size of your dashboard from the layout section.
- You can adjust the dimensions of your dashboard, give color to the border of each tile, and also change the background color of the KPI dashboard.
- The final result would look something like this dashboard.
That was all about creating a tableau KPI dashboard on Tableau Desktop using the sample superstore dataset. This helps you track the key indicators that may impact your product or business performance. And, because these KPIs are calculated fields, they give you more information about multiple variables in a single visualization.
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