In this Tableau tutorial for beginners, you will learn Tableau online from the basics. Tableau is a powerful business intelligence and data visualization tool. It is extensively used for creating and distributing highly interactive and powerful reports and dashboards that depict the data in a visually appealing form like trends, variations, charts, graphs, plots, and so on.
Tableau tutorial will be covering the following topics:
With data serving as the brick and mortar of modern-day organizations, it has become inevitable for them to make the maximum sense of data sources. However, data is made available in its complex raw form. Therefore, understanding it with the basic human eye becomes difficult. This is where Tableau comes in. This effective Tableau data visualization tool takes in data and generates intuitive reports based on data inputs. Many successful enterprises are using Tableau. The average salary of a Tableau expert is around $106,000.
Watch this Tableau Full Course In 8 Hours Tutorial:
Tableau can connect to a large number of files, relational and big data files to acquire and process the data. The tableau tool can blend all types of data like relational, unstructured, and big data sources for acquiring and processing data.
In this Tableau for beginners’ blog, you will learn Tableau which makes it easy for business professionals to work with real-time collaboration and makes it easy for analysis. Tableau is a distinct leader in the business intelligence and analytics platform as per the Gartner Magic Quadrant.
Prepare yourself for the industry by going through this Top Tableau Interview Questions and Answers!
What is Tableau?
Tableau is one of the top business intelligence and analytics tools as confirmed by none other than Gartner. The success story of Tableau is really inspirational. It is extensively used by organizations to make sense of data in a visually insightful format. Tableau can work with any kind of data be it structured, unstructured or semi-structured. Also, Tableau is able to connect with a lot of other tools, platforms like Hadoop, R Programming, and so on. You don’t need any technical knowledge to learn Tableau.
||What makes Tableau unique
||No technical skills needed to work with Tableau
|Get fast answers
|Types of data
||Tableau can work with any type of data
In this Tableau dashboard tutorial, you will get a step-by-step understanding of this top business intelligence and tableau data visualization tool.
Using Tableau, you can answer any business question provided the data exists for it in some format. Tableau has scores of features using which you can dice and slice the data and then convert it into stunning visualizations. Once the data is depicted in the form of bars, charts, graphs, plots you will be able to shed more light on the same data. You can detect hidden patterns, relationships, trends, and new meanings so that you can make a well-informed and valuable business decision.
Watch this video on What is Tableau 10?
This is the most important topic that every Tableau Tutorial has. Below are some of the features of Tableau that makes it different from other Business Intelligence tools:
Tableau connects with multiple data sources and supports larger datasets for accurate visualization. It uses a drill-down approach to reach that reveal the relationship between the independent variables. Also, the user can jump between different visualizations without any problem.
Compared to other Data Visualization tools, Tableau enables the user to show the relationship between different data variables using the various shapes, figures, labels, colors, etc.
Tableau can connect with more data sources and handle huge datasets without affecting the performance of the data engine. In addition, augmented analytics helps users with different skill sets perform data cleaning and visualization.
Tableau has many ways to find out the solution to the questions asked by the user. From basic trends to advanced ‘what if’ queries, Tableau has the best features for data discovery and predictive analytics.
Tableau has a growing community of experienced data scientists and business analysts from all around the world. Unlike other BI tools, you can easily find the solution to the problems you’re facing in Tableau without having much trouble. Also, you can grasp knowledge on Tableau through various open-source projects on GitHub.
To save your time and efforts in Tableau, you can create processing and apply the same
Calculations on different visualizations. For example, you can create a field by adding a formula and applying it to all the rows in that data source. For recurring processes, it’s an easy and effective way of creating visualizations.
Tableau supports most data sources which make it easier to connect, clean, and identify hidden patterns in the raw data. It can access large datasets and from both On-premise and On-cloud sources without stressing out the system. It supports both the live connection and the In-memory data extraction process.
In live connection, the data gets refreshed periodically and the visualizations get updated accordingly. Whereas, In-memory loads up the entire dataset in the Tableau interface and proceed to the visualization process.
Importance Of Data Visualization
Data visualization in Tableau is an important part of the data analytics process. It helps the data scientists to present the raw information in an understandable format So much so, that even an anon-technical user can use the visualization to make better decisions. Therefore, a data scientist should master data visualization skills to better communicate with the end-users.
Data visualization allows the data scientists to effectively convey the outcome of data analysis to the end-users, which enables them to identify the hidden patterns in the data. It also helps the decision-makers to comprehend the exact situation and performance of the business, so that they can make better decisions.
To companies, visualizing the raw information enables them to discover the factors affecting their growth and the areas they want to improve. In addition, it helps them to identify the relationship between the independent variables and calculate the risks of changing them.
Below are some of the best Data visualization tools used by various enterprises around the globe:
- Tableau: Tableau is one of the top BI tools used by various organizations for data analysis, visualization, report generation, and publication. It has a simple and easy-to-use interface that allows the users to connect, clean, and transform the raw data into meaningful insights. Tableau can connect with both On-premise and On-cloud data sources such as Excel Spreadsheets, CSV files, Open Database Connectivity(ODBC), Oracle, Azure, Google BigQuery, etc. Tableau is used by many companies for tasks such as sales data analysis, consumer segmenting, tracking budget expenses, customer behavior analysis, categorizing data, predictive modeling, etc.
- Excel: Excel is a popular spreadsheet application that carries some of the best visualization tools under its hood. A skilled professional can perform complex calculations and data visualization in Excel.
For internal use, Excel can be used to quickly explore the information stored in spreadsheets and visualize it in the form of charts and graphs. However, it is limited in terms of data connectivity and graphics used to create professional reports and dashboards.
- Microsoft Power BI: Power BI is yet another powerful tool used by various companies to implement BI capabilities. It’s a collection of various tools and techniques that allows the user to perform data analytics and visualization to make visually interactive reports and dashboards.
Power BI uses AI tools such as Power Query and Power Q&A that allow the user to visualize raw information and create highly customized reports. Even non-technical users can use Power BI to find hidden patterns in business data. There are differences between Power BI and Tableau. Like Power BI has Regular charts, graphs, and maps whereas Tableau supports any kind of charts, bars, and graphs.
- Domo: Domo is a cloud-based BI platform that allows the business to perform data analytics and make data-driven decisions for better performance. Domo’s business cloud is an open-source platform that connects the user with varied sources of both structured and unstructured data.
Domo provides the ability of real-time data visualization which can be used to create live dashboards and reports. The excellent UI features enable the user to create an interactive display with sparklines, dashboards, and useful widgets.
- QlikView: Qlikview is a real-time operational BI environment used for visual data analytics. Compared to other BI tools, Qlikview cannot perform the same level of visualization. However, you can analyze your data in multiple dimensions with the help of its dynamic models.
Qlikview provides multiple ad hoc queries that result in quick decision-making and easy access to the information. Also, it can connect with multiple data sources and combine them into single dashboards and reports by visualizing the raw information. But still, there are several differences between Tableau and QlikView. Such as, Tableau comes with easy drag and drop, and graphical inputs become easy too whereas, in QlikView, it is needed to write the logic for the areas where graphical changes are required.
Applications of Tableau
Tableau is such a powerful tool that it can be used in any industry since the best part is that Tableau can work with any kind of data. So here in this Tableau for beginners blog, we will list some of the applications of Tableau in the real world.
- Come up with quick visualizations and insights on disparate sources of data
- You can leverage the power of your databases& optimize query performance
- Work with statistical analysis like trending and forecasting features
- Deploy extreme data discovery and come up with unknown insights
- Easily connect with computer programming languages for powerful table calculations
- Work with data in the most intuitive, interactive manner through Tableau dashboards
Learn more about Tableau in this Tableau training in New York to get ahead in your career!
Why should you learn Tableau?
Tableau is one of the most demanded business intelligence tools in the industry today. So due to the widespread use of this top data visualization tool, there is a shortage of professionals who can work with this tool. Thus, the salaries for Tableau professionals are among the best in the IT industry. This is one of the most powerful reasons why you should learn Tableau. Other than that, you should learn Tableau online for the following reason:
- Data visualization and predictive analytics are the norm in every industry today
- Tableau can work with any data warehousing and ETL tool making it highly versatile
- Tableau is constantly updating making the future for a career in Tableau highly promising
- Tableau has a big growing community thus making it easy to learn Tableau and excel
- You don’t need any specialized skills or programming languages for learning Tableau.
If you have any doubts or Queries related to Tableau, get it clarified from Tableau Experts on Tableau Community.
Tableau Product Family
There are different Tableau products that work in conjunction and help the user seamlessly transfer the data and create data visualizations and generate reports. Below are the Tableau products or components:
Tableau Desktop allows the user to connect the data from different sources and build, dashboards, stories, and workbooks, With the Tableau Desktop and website, you can share all the insights with other users and publish the workbooks on the Tableau site.
On Tableau Desktop, the user can run direct queries on the datasets without writing the codes. You just have to write the columns you want to include and type in the visualizations such as a chart, table, graph, and map. Moreover, Tableau Desktop combines multiple views from varied data sources in single dashboards.
Tableau Server is used for publishing the reports and workbooks created on the Tableau Desktop. It enables the user to access workbooks and reports from anywhere in the world.
With Tableau Server, you can access the latest content and gain live access to workbooks and reports generated by other users. Also, the administrator of the Tableau Server can set authorization on certain projects, views, workbooks, and data sources to maintain security.
It’s a free application that you can install on your desktop and use to view the data visualizations built by the users on Tableau Desktop. On Tableau Reader, you can view, interact, add different types of filters, and drill down the data without altering the original datasets and visualizations.
This Tableau Public tutorial also demonstrates how it’s free software that anyone can use to analyze the data and create visualizations. You can create workbooks or reports and save them in the Tableau Server, but anyone can see those visualizations as its open for everyone.
Tableau Online is a cloud platform that makes it easy to publish and share the dashboards with other users. It helps you and your colleagues to work on a project and extract valuable information that can convert them into visually interactive workbooks. These visuals can be accessed by the website, Tableau Desktop, and Tableau mobile applications.
How is Tableau helpful for Data scientists? Learn through our blog on Tableau for Data Scientists now.
How To Use Tableau
Tableau tutorials cover this subject extensively. In order to use Tableau Desktop effectively for data visualizations, three simple steps need to be followed:
- Connect the data
- Play around with the Interface
- Create data visualizations
Connect the Data
On the left side of Tableau Desktop you will have the ability to link data sources from various locations – both local files and servers can be connected.
Some of the Tableau supports various data sources such as Excel spreadsheets, local databases, statistical, text, and CSV files. You can also connect with the data servers like the Tableau Server, Google Analytics, Google BigQuery, Hadoop Hive, Oracle database, MySQL, IBM DB2, and SAP at higher speeds.
After connecting the datasets, you can play around with your data, clean it, and integrate various datasets for better insights.
Go through our blog on Tableau Parameters to learn more in detail
Play around with the Interface
After loading your datasets, an interface will appear on the screen with various features and datasets. Below is the image of the user interface where you can play around with your data and proceed to the workbooks section from the bottom left corner.
The workbook interface will show all the features required to create stunning visualizations. The variables of your datasets will appear on the left side and visuals being on the right side under the Show Me section.
Now, you can select the data variable and Tableau will highlight the visualizations compatible with the variables. For example, Tableau will highlight the maps and geographical visuals if you select a country variable.
The table below shows the appropriate applications of the popular visuals:
||Mainly used for continuous dimensions
||Used when the dimension is not continuous
|Dual Axis Graph
||Used to present two different variables or measures together
||Used to measure the sales and other plots on geographical maps
||Used to compare the measures
||Used to present the quantities in nested rectangles
||Used for measuring the variations across various categories
Data scientists utilize Tableau to craft dynamic and engaging reports that are easily understandable by almost anyone. With its variety of charts, graphs, and maps for analyzing business data analysis purposes; Tableau charts help visualize data according to requirements while simultaneously presenting it.
Below is the selection of Tableau Desktop charts available:
- Text Label: These charts allow for creating crosstabs or Pivot data by placing dimensions into columns and rows respectively, whilst Heat Maps show data in tabular format using various colors.
- Highlight Table: Highlight tables are used to visually display categorization using color. Symbol Maps: Used to visualize geographical data using bubbles. Maps: Visualizing geographical data displayed on maps.
- Pie Chart: Used to represent data with multiple variables/dimensions. Horizontal
- Bars: Primarily utilized when comparing one dimension against another – for instance sales over different years.
- Horizontal Bars: Horizontal bars are generally used to compare two dimensions; for instance, charts that compare sales in various years use this format.
- Stacked Bars: Extended horizontal to add multiple dimensions. Side-by-Side Bars: Used to compare independent variables by grouping them together.
- Circle View: This format displays numerical data in circles instead of bars.
- Line Charts are commonly used to display recent trends, demand or sales figures for products and services.
- Dual Lines allow comparison between multiple products or trends while an Area Chart graphically represents their quantitive information.
- Discrete Area Charts: Used to display quantitative data in discrete areas. Scatter Plot: Used to visualize relationships between two variables and create regression models. Histogram: Visualizing statistical data within a certain range.
- Gantt Chart: Used to determine the duration of any activity or event.
- Bullet Chart: An easy way to compare various measures and dimensions visually.
- Bubble Chart: Used to compare two variables by representing them visually using bubbles, for instance higher sales in certain regions will appear as larger bubbles than areas with fewer sales.
Learn about the difference between Tableau’s Heatmap and Treemap in our blog at Tree Map vs Heat Map!
Tableau maps are an effective and straightforward way of visualizing geographic data, particularly two or more dimensions simultaneously. Below is a selection of popular Tableau maps used for various applications:
- Proportional Symbol Maps: Proportional symbol maps are an effective way to visualize quantitative data for specific locations. Here, multiple quantities or variables per location may be represented as proportional symbol maps – for instance Earthquakes that occurred over the past decade with their magnitude might make an effective example.
- Choropleth Maps: Commonly known as filled maps, choropleth maps represent statistical or ratio data of geographic areas in a visual form, sharing patterns with each area represented. They can be used to depict climate changes, pollution levels, gender distribution or literacy rates between various nations or the entire globe.
- Point Distribution Maps: Point Distribution maps depict data points shared among specific locations. They’re also useful in visualizing events that happened at specific times; to create these distribution maps, your data source must contain details about their latitude and longitude coordinates.
- Heat Maps (commonly referred to as density maps) are useful tools for visualizing large volumes of data and spotting trends that help inform better decision-making. You could create one to depict your website data and see where users are accessing your site from different places.
- Flow Maps in Tableau: Flow or path maps in this context depict the journey or path taken by something from one place to another; an ideal illustration would be a hurricane’s flow map from its origination point to completion over a certain period.
- Spider Map: Spider maps are popularly known as origin-destination maps, depicting multiple destinations from one origin or location. An ideal use case would be depicting migrants’ data as they travel between areas or countries.
Tableau Top Features and Strengths
Here we list some of the most important strengths and salient features of Tableau which makes it a highly desired tool in the corporate world today:
- Highly interactive tableau data visualization
- Easily implementable
- Handling large amounts of data
- Use of other scripting languages
- Responsive dashboard and support
- Different products for different users
- High-performance technology
- No need for any technical expertise.
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Tableau learning provides solutions for all kinds of industries, departments, and data environments. Following are some unique features that enable Tableau to handle diverse scenarios.
- High-Speed Analysis: High-speed analysis requires advanced programming knowledge. Once you have access to data, you can begin extracting value from it.
- Reliable: Data analysis software does not require complex installation procedures to work effectively, with most people opting for desktop versions to start and complete data analyses.
- Visual Discovery: Tableau’s Visual Discovery feature makes data exploration and analysis effortless by providing numerous charts, colors, trend lines, graphs, etc. All aspects can be managed easily using drag-and-drop and very minimal scripting is necessary.
- Blending Diverse Data Sets: With this software, you will be able to combine various types of data sets such as relational, non-relational, structured and semi-structured sets without needing to integrate or understand how this information is stored.
- Device Independent: Tableau is designed to work smoothly across different kinds of devices, so no worries are necessary about software and hardware configurations. And Collaborate Real-time: It lets you collaborate in real-time with colleagues to produce stunning visualizations together.
- Real-Time Collaboration: Tableau can enable real-time data collaboration by filtering, sorting and discussing data live in portals such as SharePoint site or Salesforce. You can save your view of data while simultaneously subscribing colleagues to subscribed interactive dashboards so they receive updated views every time they refresh their browsers.
- Centered Data: The Tableau Server offers an easily manageable way for organizations to keep all of their published data sources updated, from deletion, modification, addition of tags and schedule management – to extract refreshes on both incremental and full refresh schedules. Administrators can centrally define schedules on this server to facilitate this task.
To take Tableau advantage, enroll in Tableau Certification now.
Recommended Audience for this Tableau Tutorial
This step-by-step Tableau tutorial for beginners is designed for all those learners who want to grasp knowledge on tableau for free and work in the business intelligence domain. Anybody who wants to be in data analytics, data visualization, project managers can go through this Tableau Desktop tutorial for beginners, and learning tableau will become easy. There are no prerequisites as such to learn from this Tableau basic tutorial.
If you have a basic idea of various visualization options like graphs and charts, then it is beneficial. While going through the Tableau topic, you must have come across a few important questions related to tableau such as Is Tableau easy to learn,”What are the Tableau tools?” and Can I use Tableau for free?
Let me clarify all these questions for your better understanding.
Is Tableau easy to learn?
Tableau is one of the fastest evolving data visualization tools which is majorly used in BI i.e. Business Intelligence industry. It is very fast to deploy, easy to learn, user-friendly, and very intuitive to use for a customer
What is the Tableau tool?
Tableau is an emerging powerful and fastest-growing data visualization tool that is widely used in the Business Intelligence Industry. It helps to simplify raw data into a very easy and understandable format. Tableau does data analysis very fast and the visualizations created are in the form of dashboards.
Are you interested in learning the Tableau certification course in Bangalore from Experts?
Can I use Tableau for free?
Tableau Public is free software that allows you to connect to a spreadsheet or file and you can also create interactive data visualizations for the web. Tableau Reader is also free and allows you to open and interact with data visualizations that are built-in Tableau Desktop