Understanding Tableau Data Integration Simplified 101

Business Intelligence tools allow organizations to visualize their data in the form of dashboards, enabling them to derive meaningful insights and maximize revenue outcomes. One of the most well-known Business Intelligence tools is Tableau.

Using Tableau Integration with other platforms or data sources such as Data Warehouses, CRMs, Ads Platforms, etc. helps companies get useful insights from the data and easily generate reports.

This article will provide you with an in-depth understanding of how Tableau Data Integration works along with how you can import your data into Tableau from various data sources.

What is Tableau?

Tableau is one of the most powerful and fastest-growing Data Visualization and Business Intelligence tools available in the market. It allows users to seamlessly transform raw data into a visual format that can be understood by anyone.

The various tiers offered by Tableau are as follows:

• Tableau Desktop
• Tableau Public
• Tableau Online
• Tableau Server
• Tableau Reader

Tableau is widely used as it allows users to analyze the required data seamlessly. Visualizations in Tableau are generated as Worksheets, Dashboards, and Stories. Users can create custom dashboards that provide actionable insights and help drive the business forward. When configured with the proper underlying hardware and operating systems, all products by Tableau always operate in virtualized environments. Tableau can be used to explore data with limitless visualizations.

Benefits of Tableau

Business Intelligence processes play a key role in the organization of data which makes it easier to access and analyze the data. The decision-makers can accordingly make an educated decision after digging into the customer data to extract actionable insights. Here are a few benefits of Tableau:

• Increased Organizational Efficiency: It allows you to benchmark the results against the larger organization through a holistic view of your operations. This lets you discover the areas of opportunity.
• Improved Customer Experience: Tableau plays a very important role in affecting customer experience and satisfaction. Here is an example to display its tangible effect.
• Improved Employee Satisfaction: Previously, the Data Analysts and IT departments spend a very small amount of their time responding to the requests of business users.
• Competitive Edge: The knowledge of one’s position in the market and one’s performance enables an organization to be more competitive.

Data Types in Tableau

Tableau works with seven different types of data. The data type identifies the type of data contained in a certain field.

Data Prep, Data Blending with Tableau

Data Preparation

You can have as many connections to as many different Data Sources as you like in a Tableau workbook, and you can utilize them all to generate unique visualizations that can be integrated seamlessly on a dashboard. You may build seamless interactivity for the end-user by using action filters and cross-database filters.

Users will be happy to see financial data from your general ledger system and customer data from your CRM in a single dashboard, your boss will be impressed with how quickly you built it, and you’ll smile to yourself as you remember how simple it was to connect everything and bring it all together with a few clicks.

Data Blending

“Data blending” is a Tableau technical term for combining two different data sources in a single visualization. Data blending is done at an aggregate level, unlike joining, which is done row by row. This novel technique was first introduced in Tableau 6 and has since been refined.

Tableau’s data blending feature allows you to perform excellent visual analyses with diverse data and provides the following benefits:

• Data from two or more big data sets can be combined without having to link them row by row. In an enterprise data warehouse with huge fact tables, this can be extremely valuable. Tableau can be used to blend the data at an aggregate level rather than combining them together. This can boost performance and give you a lot of data model flexibility.
• Control the aggregate level. Is there a record for every client for every day in one of your data sets, and monthly targets in another? If you combined those two sets, you might get a bunch of monthly numbers that are duplicated, but when you use data blending, your monthly values come through precisely.
• Let your imagination run wild. Because data blending occurs concurrently with data visualization, it is less of a data preparation stage and more of a “real-time” data experience. You can get really creative and modify the level of aggregation on the fly with a parameter or blend different time periods for period-over-period comparisons.

Tableau Integration Data Sources

Tableau houses numerous connectors that are built and optimized for a vast number of files and databases. The list of supported Tableau Data Connectors ranges from PDFs and Spreadsheet applications such as Microsoft Excel to various Big Data, and Relational On-premise or Cloud Databases such as Google BigQuery, MySQL, etc to various Web Data Connectors that allow developers to integrate user’s Tableau Data with complex and dynamic data on the web.

You can also check our article on Tableau AWS Deployment.

The following image shows the list of connectors supported by Tableau:

Tableau Data Source connectors allow users to connect with a variety of data sources which are as follows:

• Tableau Data Connectivity to a File
• Tableau Data Connectivity to a Server

1) Tableau Data Connectivity to a File

The steps to connect a Text file with Tableau are as follows:

• Step 1: Select Text file/Microsoft Excel or any other file as per requirement from the Data tab in the upper left corner.

• Step 2: Browse to the Text/Microsoft Excel or any other file that you wish to open in Tableau using the File Browser and click on Open.

• Step 3: The Text/Microsoft Excel or the file of choice will be imported and can be accessed from the Connections pane on the left.

2) Tableau Data Connectivity to a Server

You can connect Tableau with your desired database by implementing the following steps:

• Step 1: Select MySQL or any other Database/Server as per requirements from the Data tab found in the upper left corner.

• Step 2: Enter the required credentials to access the Database/Server and then click on Sign In.

How does Tableau work?

• Tableau supports integration with almost all the data sources. One can use Tableau to extract data from any platform and analyze it. Pulling data from simple CSV files, PDFs, spreadsheets to complex Databases such as Oracle and Cloud Databases and Data Warehouses can easily be accomplished with the help of Tableau.
• Tableau keeps developing new data connectors to provide more data accessibility and flexibility to users. Depending on the version of Tableau that you have, the number of supported data connectors varies.  
• All the data extracted by Tableau can be connected live or extracted to Tableau’s data engine to a Tableau Desktop. After receiving the information, Data Analysts, Data Scientists, Business Analysts can pull this data and generate visualizations from it to get insights from the data. 
• Tableau offers many customizable and pre-built dashboards for different use cases, and users can also build design dashboards from scratch. All the data get visualized on these dashboards. The dashboards are shared with the users as a static file, and users view the dashboards using Tableau Reader.
• Tableau Server is an enterprise platform that handles distribution, collaboration, governance, security, automation features, models, and users can publish data from Tableau Desktop to the server.

Tableau Uses

In this section, you will go through some of the applications and uses of Tableau. Some of the main uses of Tableau are listed below:

• Data Blending
• For managing the metadata of large and complex datasets
• For query translation into intuitive visualization
• Data Visualization 
• Businesses Intelligence 
• Data Collaboration 
• Real-time Data Analysis 
• For importing large datasets

Connecting to Data in Tableau

You can connect Tableau to multiple data sources such as Excel files, text files, database management systems, and even cloud storage. You can then pull data from there and use it to create visualizations. 

The process of connecting to data sources differs from one product to another. In the Desktop version, there is the “Connect” option on the left side of the window. Below this option is the different data sources that you can connect to. 

You simply have to select the data source that you need to connect to. You will be taken through on-screen instructions to establish a connection to the data source. Once the connection has been established, you can pull data into it for visualization. 

To connect to the Server product or the Online product from Tableau Desktop do the following steps:

• Step 1: Click the “Tableau Server” option located below “Search for Data” under Connect. 
• Step 2: A small window will pop up. To connect to the Server product, simply enter the name of the server and click Connect. 
• Step 3: If you need to connect to the Online product, simply click the “Tableau Online” option located below Quick Connect. For the Server product, use your username and password to sign in. For the Online product, use your email address and password.  
• Step 4: You can then select the data source that you need to connect to. 
• Step 5: If you are using the Server or the Online product of Tableau, you will create the connection using a web browser. You can find the Tableau Catalog in the Data Management Add-on. If you enable it in your environment, you’ll be able to connect to tables and databases from Search for Data results on the Desktop product. 

What are Tableau Data Extracts?

Tableau data extracts are a “snapshot” of data that is compressed, stored, and loaded into the memory. Tableau Data Extracts (TDE) has two design aspects. The first one is that TDE is a columnar store which means that all the data is stored in a columnar fashion in a database. The next aspect is their structure which impacts the memory storage in tableau.

Integrating Unsupported Tableau Data Sources

Although Tableau supports direct integration with 80+ data sources, there are still a wide variety of data sources that are not directly supported by it. To help users establish connections with unsupported Tableau Data Sources seamlessly, the following functionalities were introduced:

• Web Data Connector
• ODBC Connector
• Extract API
• Hyper API

1) Web Data Connector

Tableau Web Data Connector (WDC) can be defined as a set of APIs that allow developers to establish a connection between Tableau and any data on the web that is accessible over HTTP. Web Data Connector (WDC) is an HTML file that includes some JavaScript code.

Tableau houses an intuitive functionality that allows users to create their own Web Data Connector (WDC) or use an existing one. Users can create their own Web Data Connector (WDC) that is capable of reading data from any website publishing data in XML, JSON, or HTML format.

The Web Data Connector (WDC) must be hosted on a local Web Server on your computer, on a Web Server in the user’s domain, or on any third-party Web Server.

Users can implement the following steps in order to leverage Web Data Connectors to set up unsupported Tableau Data Integrations:

• Step 1: Open Tableau, click on More Servers in the Connect pane, and then select Web Data Connector.

• Step 2: Enter the URL of the WDC and press Enter.

• Step 3: If the WDC leads to a webpage, enter any required information and select Submit.
• Step 4: Once you’ve provided the required information, WDC will retrieve all the information as an Extract and import it into Tableau Data Connections. This data can then be analyzed as per the usual process.

2) ODBC Connector

ODBC (Open Database Connectivity) is a popular industry standard that allows a wide variety of software applications to access data stored in a database. The basis of ODBC is that software applications can make use of standard SQL queries to form a connection with a database and request data from it.

The ODBC driver accepts requests in the standard syntax and converts these requests into a format that can be interpreted by the target database. Hence, the ODBC driver can be seen as a translation layer capable of converting a general-purpose request into a database-specific format.

Tableau houses functionality that allows users to connect with all ODBC-compliant data sources using its robust in-built ODBC Connector. This ODBC Connector can be leveraged to seamlessly integrate unsupported Tableau Data Sources by implementing the following steps:

• Step 1: Open Tableau, click on More Servers in the Connect pane and then select Other Databases (ODBC).
• Step 2: Enter the required information required to identify and establish a connection with the necessary ODBC-compliant database and click on Sign In.

3) Extract API

The Tableau Extract API houses functionalities that allow users to perform the following operations:

• Create and add data to Extract files that can improve performance exponentially and provide uninterrupted offline access to all your Tableau Data Sources.
• Write programs capable of integrating with unsupported Tableau Data Sources, and writing data into Extract files for later use.
• Write programs capable of creating Extract files that contain data from multiple tables.

The platforms supported by Tableau Extract API are as follows:

• Windows 7 or later.
• Windows Server 2008 R2 or later.
• Mac OS X (10.9 and later).
• CentOS 7 and later.
• Fedora 18 and later.
• Ubuntu 12.04 and later.

The programming languages supported by Tableau Extract API are as follows:

• C/C++
• Python 2.x and 3.x
• Java

4) Hyper API

Tableau Hyper can be seen as a high-performance In-memory Data Engine technology that allows users to analyze large and complex datasets faster, by seamlessly evaluating all analytical queries in the transactional database.

Users can leverage the Tableau Hyper API to perform the following operations:

• Open existing Extract files.
• Perform various CRUD (Create, Read, Update, Delete) operations on Extract files.
• Create Extracts for various unsupported Tableau Data Sources.
• Automate various custom Extract, Transform and Load (ETL) operations.
• Use SQL queries to interact with data in Tableau Hyper Extracts.

The platforms supported by Tableau Hyper API are as follows:

• Microsoft Windows Server 2019, 2016, 2012 R2, 2012, 2008 R2
• Microsoft Windows 7 or newer (64-bit)
• Amazon Linux 2, Red Hat Enterprise Linux (RHEL) 7.3+, CentOS 7.3+, Oracle Linux 7.3+, Ubuntu 16.04 LTS, and 18.04 LTS
• macOS 10.13 or newer

The programming languages supported by Tableau Hyper API are as follows:

• Python (3.6 or newer)
• Java (Java 8 or newer)
• C++ (C++11 or newer)
• C#/.NET (.NET Standard 2.0)

Conclusion

This article provided you with an understanding of how Tableau Data Integration works along with various data sources from which data can be imported into Tableau irrespective of whether they are directly supported by it or not.

Choosing a Business Intelligence and Data Analysis tool for your business can be a tough decision primarily because almost all departments in a business now make use of multiple platforms to run their day-to-day operations and there is no single tool that can integrate with all these sources easily.