Tableau is renowned for its intuitive interface, which enables even non-technical users to generate informative reports and dashboards. This makes it more applicable to a wider range of positions within an organization. Thrive in your data visualization career by gaining fundamental understanding with this Tableau Software Tutorial. Get started with our Tableau course syllabus and explore our Tableau project for resume.
Introduction to Tableau
Tableau is a robust and quickly expanding visual analytics tool that aids individuals and businesses in viewing and comprehending their data.
- It allows users to examine trends, patterns, and insights by distilling complex data into simply comprehensible representations.
- Tableau is renowned for its intuitive user interface and capacity to generate shareable and interactive dashboards without the need for complex code.
Uses of Tableau
Tableau is utilized for a wide range of applications by diverse roles and sectors, such as:
- Data Visualization: Making a variety of interactive charts, graphs, maps, and dashboards to visually represent data.
- Business Intelligence: Analyzing corporate data to obtain knowledge, monitor Key Performance Indicators (KPIs), and make informed decisions.
- Data Exploration: It enables users to examine their data in great detail, spot patterns and anomalies, and comprehend the connections between various data points.
- Dashboards & Reporting: Creating thorough reports and real-time dashboards to track performance and effectively convey findings.
- Forecasting and Predictive Analytics: Making predictions and identifying future trends by applying its analytical powers.
- Data Blending: Combining information from several sources to obtain a comprehensive picture.
- Geospatial Analysis: Visualizing location data to identify geographic trends.
Use Cases of Tableau
Typical use cases in several areas consist of:
- Sales: Estimating future sales, evaluating consumer behavior, and monitoring sales performance.
- Marketing: It includes market segmentation, consumer interaction analysis, and campaign effectiveness measurement.
- Finance: Risk analysis, financial reporting, and budgeting.
- Human Resources: Examining indicators related to hiring, employee satisfaction, and staff turnover.
- IT: Keeping an eye on resource allocation, system performance, and security compliance.
- Healthcare: Examining public health trends, resource management, and patient outcomes.
- Manufacturing: Quality control, supply chain optimization, and production efficiency monitoring.
Benefits of Tableau
Some of the advantages of Tableau:
- User-Friendly Interface: Users with different levels of technical expertise can generate stunning visualizations due to its user-friendly drag-and-drop interface.
- Interactive Visualizations: It allows users to delve down into specifics, analyze data dynamically, and obtain deeper insights.
- Speed and Performance: It is able to effectively manage big datasets, offering prompt insights without sacrificing efficiency.
- Wide Range of Data Connectivity: It connects to a number of data sources, such as big data platforms, cloud services, spreadsheets, and databases.
- Real-time Analytics: It allows for real-time data analysis, offering current insights for prompt decision-making.
- Collaboration and Sharing: It encourages data-driven collaboration by making dashboard and report sharing simple.
- Advanced Analytics: It provides capabilities for trend identification, forecasting, and clustering and integrates with sophisticated statistical tools.
- Mobile Accessibility: It offers mobile applications for dashboard access and interaction while on the go.
- Strong Community and Support: A sizable and vibrant community offers a wealth of best practices, resources, and assistance.
Tableau is a flexible and strong platform that democratizes data visualization and analysis, enabling people and businesses to better understand their data and make more informed decisions.
Recommended: Tableau Online Course Program.
Tableau Interface
The Tableau interface is made to be easy to use and intuitive. A few important places are usually visible when you launch Tableau Desktop:
Start Page: The first screen you see is this one. It enables you to access instructional resources, open recent worksheets, and connect to data.
Data Source Page: This is the page you will see after connecting to a data source. This is where you can:
- In the left pane, view the linked data sources.
- To join or union tables, drag & drop them.
- Use the data grid at the bottom to preview your data.
- In Tableau Desktop, select between Live and Extract data connections.
Workspace (Sheet View): You build your visualizations here. It is made up of various significant parts:
- Menu Bar: With choices including File, Data, Worksheet, Dashboard, Story, Analysis, Map, Format, Window, and Help, the menu bar is located at the very top.
- Toolbar: It is located beneath the menu bar, offers easy access to frequently used functions including saving, undoing or redoing, and creating new worksheets, among others.
- Data Pane (left): The tables and fields from your linked data sources are listed in the Data Pane (left). Fields are divided into two categories: Measures (quantitative data) and Dimensions (qualitative data).
- Analytics Pane (left, next to Data): Trend lines, reference lines, and forecasts are just a few of the analytical objects that may be added to your view using the Analytics Pane (located next to Data on the left).
- Shelves (Columns, Rows): These are the horizontal sections above the view where you can specify the structure of your visualization (e.g., what goes on the x and y axes) by dragging and dropping fields from the Data pane.
- Marks Card (left): It manages the visual characteristics of the data points that are visible to you, including their size, color, tooltips, labels, and shape.
- Filters Shelf: To filter the data displayed in the view, drag and drop fields in it.
- Pages Shelf: This feature lets you create a form of animation by segmenting the view into a number of pages according to the values in a field.
- “Show Me” (top right): It makes recommendations for various chart kinds depending on the fields you’ve chosen.
- View Area (center): The primary location for creating and displaying your visualization.
- Status Bar (bottom): It gives details about the data and view that are now displayed.
- Sheets, Dashboards, Story Tabs (bottom left): You can switch between individual spreadsheets, dashboards (groups of views), and tales (sequences of visualizations) using it.
Tableau converts your data into visual representations in the view area when you connect to it and drag and drop fields onto the shelves and the Marks card.
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Connecting to Data with Tableau
A Connect pane will appear on the left side of the Start Page when you launch Tableau Desktop. Tableau offers a list of several data connectors here, divided into:
To a File:
- Excel: Connect to.xlsx and.xls files in Excel.
- Text File: Attach to delimited text files, such as.csv and.txt files.
- JSON File: Establish a connection to JSON-formatted data.
- PDF File: Establish a connection with tables in PDF documents.
- Spatial File: Connect to geographic data in forms such as shapefiles using a spatial file.
- Statistical File: Open files from statistical programs such as SAS (.sas7bdat,.sas7b7dat) and R (.rda,.rdata).
- More: Connects to different file formats by opening a file browser.
To a Server:
Numerous database and internet service connectors are listed in this section, such as:
- Relational Databases: They include, among others, MySQL, PostgreSQL, Oracle, Microsoft SQL Server, Amazon Redshift, Snowflake, and Google BigQuery.
- Cloud Data Sources: They include Google Cloud SQL, Azure SQL Database, and Amazon Athena.
- Business Applications: Such as Google Analytics, Salesforce, and Marketo.
- Tableau Specific: Tableau Server
- Web Data Connector: You can create unique connections to web-based data sources with the help of a web data connector.
- ODBC (Open Database Connectivity) and JDBC (Java Database Connectivity): For connecting to databases that Tableau does not natively support, use them.
The Connection Process:
Select your connector: Click on the type of data you wish to connect to (such as “Excel” or “Microsoft SQL Server”) in the “Connect” box on the Start Page.
Provide details:
- For files: To choose the file, you will usually browse.
- For servers: You must input connection information such as the database name, server name, and your login credentials (password and username).
Data Source Page: You will be directed to the Data Source Page after the connection has been made. This is where you can:
- Examine the sheets or tables that are accessible in your data source.
- If you’re dealing with many tables, you can union or join them by dragging and dropping them onto the canvas.
- Examine the data in advance.
- Select between an Extract (a snapshot of the data saved in Tableau’s fast data engine) and a Live connection (a real-time query of the data source).
Live vs. Extract Connection:
- Live: Offers data in real time. When the underlying data source changes, Tableau instantaneously updates to reflect those changes. Ideal for data that changes regularly and when you have a dependable and quick database connection.
- Extract: Make a copy of the information. Because Tableau uses the local copy, this can enhance performance, particularly when dealing with big datasets or sluggish connections. It is possible to schedule the refresh of extracts.
You are prepared to go to a worksheet and begin creating visualizations using the fields from your data after you have established your data connection and configured it on the Data Source Page.
Related: Power BI Tutorial for Beginners.
The Data Pane in Tableau
The fields from your linked data sources that you will need to construct your visualizations are located and managed in this important section on the left side of your worksheet view.
Usually, the Data Pane is divided into many important sections:
The Connected Data Source(s): The name or names of the data sources you have connected to are displayed at the very top. All of your connections will be mentioned here if you have more than one.
Search Bar: You may easily locate particular fields by name using the search bar that is typically located above the list of fields. When working with datasets that contain a lot of columns, this is really beneficial.
Dimensions: You may find the Dimensions under the search bar. These are often qualitative, category data. Your data is described and categorized by them. Among the examples are:
- Product Name
- Customer Segment
- Region
- Date fields (often treated as dimensions initially)
- Dimensions are usually represented by a blue icon Abc
Measures: The Measures are located directly beneath the Dimensions. Usually, these are numerical, quantitative data that can be combined (averaged, totaled, etc.). Among the examples are:
- Sales
- Profit
- Quantity
- Number of Customers
- Measures are usually represented by a green icon #.
Sets: Any custom groupings of dimension members that you have developed will show up in their own area, usually above the parameters. Sets can be either dynamic or static. Typically, a Venn diagram icon is used to indicate them.
Parameters: Dynamic variables known as parameters are employed in reference lines, filters, and computations. Users can enter values that alter the visualization thanks to them. Typically, they are denoted by a little circular icon.
Key Actions You Can Perform in the Data Pane:
Drag and Drop: The main method of using the Data Pane is to drag and drop fields onto the Shelves (Rows, Columns, Filters, and Marks card). While dragging a measure usually aggregates the data (e.g., sums it up), dragging a dimension usually produces headers or labels.
Right-Click Options: When you right-click on a field in the Data Pane, a context menu with a number of choices appears, including:
- Rename: Modify the field’s display name.
- Describe: View details about the field, such as its origin and data type.
- Create: Based on the selected field, it enables you to construct parameters, groups, hierarchies, bins, and computed fields.
- Change Data Type: Change the field’s data type (from String to Date).
- Convert to Dimension/Measure: You can modify a field’s role here if Tableau classifies it erroneously.
- Default Properties: For a measure or dimension, set the default aggregations, number formats, date formats, and comments.
Organize: If you have a lot of fields, you can arrange them into folders to make the Data Pane easier to use.
The Data Pane is your Tableau inventory of data fields that are prepared for use in creating your visual analysis. Working with Tableau efficiently requires an understanding of its structure and the operations it allows.
Recommended: Data Analytics Tutorial for Beginners.
Creating Your First Worksheet in Tableau
Let’s make your very first Tableau worksheet! This is where visualization’s magic occurs. Here are the steps to begin, assuming you have already established a connection to a data source:
Navigate to a New Worksheet:
- Examine the Tableau window’s lower-left corner. If you are still on the Data Source page, you should see tabs labeled with the name of your data source and perhaps a default “Sheet 1” as well.
- Click the plus (+) symbol adjacent to the current sheet tabs to start a new worksheet. This will launch a blank view of the worksheet.
Drag and Drop Dimensions to the Shelves:
- Go to the left-hand Data Pane.
- Locate a Dimension (keep in mind that these typically feature the blue ABC emblem). “Category” is a field that you might have.
- From the Data Pane, drag the “Category” field to the Rows shelf. The distinct values from the “Category” field ought to show up in your view as rows.
Drag and Drop Measures to the Shelves:
- Find a measure now; these typically include a green # icon. Assume that the field “Sales” is one of yours.
- From the Data Pane, drag the “Sales” field to the Columns shelf.
- You will see a bar chart with each bar representing a category and its height indicating the total sales for that category after Tableau automatically aggregates this measure (typically by adding them up).
- To create a horizontal bar chart, you may also drag “Sales” to the Rows shelf and “Category” to the Columns shelf. Tableau is quite flexible!
Explore the “Marks” Card:
- Your data points’ visual details are managed via the Marks card, which is located on the left, beneath the Analytics window.
- To give your chart additional visual information, you can drag measurements and dimensions to various sections of the Marks card (such as Color, Size, Label, Tooltip, and Shape).
- To make each category on the Marks card represent a distinct color, you may, for instance, drag the “Category” dimension to Color. To show the sales value on each bar, you might drag the “Sales” measure to Label.
Use “Show Me”:
- The “Show Me” pane is located in the upper right corner of the window. Depending on the fields you have chosen in the Data Pane or have previously put on the shelves, this recommends several chart types.
- Try using Ctrl+clicking or Shift+clicking to choose one dimension (“Category”) and one measure (“Sales”) in the Data Pane, and then examine the “Show Me” options. To view the many chart types that can be used to visualize your data, click on them.
Well done! You just made your first Tableau worksheet. Your data should now appear in a simple display.
You can then further hone your perspective by:
- Expanding the Marks card’s and the shelves’ fields.
- Data filtering.
- Bars are being sorted.
- Modifying the type of chart.
- Formatting the look.
Related: MSBI Training in Chennai.
Calculations in Tableau
In Tableau, calculations are a potent tool for extracting fresh insights from your data. To carry out date computations, string manipulations, logical comparisons, mathematical operations, and more, you can create calculated fields.
This is an explanation of how Tableau calculations operate:
Creating a Calculated Field:
- Navigate to the top-level Analysis menu.
- Choose “Create Calculated Field.”
- As an alternative, you can click the dropdown arrow in the upper right corner of the Data Pane and select Create Calculated Field…. or right-click in the empty spot and select Create Calculated Field….
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The Calculation Editor:
This window will pop up, where you’ll define your calculation:
- Name: Put a meaningful name at the top of your calculated field.
- Formula Area: This is the sizable text field where your formula will be entered.
- Functions Pane (right): The functions that Tableau offers are listed in it, which is divided into different categories such as Number, String, Date, Logical, Aggregate, Table, and so on. To include a function in your formula, double-click on it. A syntactic example and description are displayed underneath the function you have selected.
- Fields List (left): The fields from your Data Pane that you can utilize in your computations are displayed in it. You can add a field to your formula by just double-clicking it.
- Error Checking (bottom): Tableau will highlight any syntax problems in your formula as you type it. If your formula has a green checkmark, it is legitimate.
Writing Formulas:
The computation language of Tableau is quite adaptable. Here are a few simple examples:
Arithmetic:
[Sales] – [Cost] // Calculates Profit
[Quantity] * [Price] // Another way to calculate Sales (if Price is available)
[Profit] / [Sales] // Calculates Profit Ratio
Logical:
IF [Sales] > 1000 THEN “High” ELSE “Low” END
String:
LEFT([Customer Name], 3) // Returns the first 3 characters of the Customer Name
Date:
DATEPART(‘year’, [Order Date]) // Extracts the year from the Order Date
Aggregation:
These can be included in computed fields, but they are frequently used directly on measures.
SUM([Sales])
AVG([Profit])
COUNTD([Customer ID]) // Counts the distinct number of customer IDs
Using Calculated Fields:
A calculated field will show up in your Data Pane after you create it. The calculation’s outcome (such as a number, string, or date) will determine whether it is classified as a Measure (green icon #) or a Dimension (blue icon boxedAbc). After that, you can create visualizations using this new feature in the same way you would any other field in your data source.
Example Scenario:
Assume that “Quantity” and “Sales” are your metrics. The “Average Selling Price” for each item is what you want to figure out.
- Go to Analysis > Create Calculated Field…
- Name of the Field: “Average Selling Price”.
- In the formula field, type
SUM([Sales]) / SUM([Quantity])
- Click OK.
You may now drag and drop the new “Average Selling Price” metric into your rows, columns, or the Marks card in your Data Pane.
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Conclusion
And that brings us to the end of this Tableau software tutorial. There is much more to discover about Tableau, a comprehensive and strong tool. We want you to explore full Tableau learning as you continue your education. Awaiting you is the world of data visualization! Come learn with us the best Tableau training in Chennai.
