Connecting Tableau Data Warehouses: 2 Easy Methods

on BI Tool, Data Warehouses, Tableau • March 31st, 2022 • Write for Hevo

Tableau Data Warehouses_FI

Data is the core aspect of any organization for effective and strategic decision-making. However, the surge in a colossal amount of data has led to data silos because organizations often rely on experts like Data Analytics and Data Scientists to gain insights and share them with decision-makers. Such dependence on experts slackens the decision-making process and results in productivity loss. To mitigate such issues, organizations can embrace the combined power of Data Warehouses and Business Intelligence tools. Since data is organized in Data Warehouses and Business Intelligence tools like Tableau can be used by non-experts, it expedites collaboration and decision-making processes. 

In this article, you will learn how to connect a Tableau Data Warehouse and understand the value of BI and Data warehousing.

Table of Contents

Prerequisites

Basic understanding of analytics.

What are Data Warehouses?

The term ‘Data Warehousing’ was coined by IBM researchers Barry Devlin and Paul Murphy in the late 1980s. The purpose of the data warehousing approach was to build an architectural model for moving data from operational systems to decision environments. Data Warehouse is a Data Management system that enables and supports Business Intelligence (BI), particularly analytics operations. 

Data Warehouses provide organizations with the broad and unique benefit of allowing them to analyze massive volumes of data. 

The four unique characteristics of Data warehouses are:

  • Integrated: Data Warehouses bring together different types of data from various sources to establish consistency.
  • Subject-Oriented: Data Warehouses are capable of supporting the analysis of data pertaining to a functional area.
  • Time-Variant: Data Warehouse helps you in examining the changes over time.
  • Non-Volatile: The data that enters the Data Warehouse remains non-volatile.

Various Data Warehouses

1) Oracle

Oracle Database was the first database designed with corporate grid computing in mind. It is one of the most adaptable and cost-effective data and application management systems available. Oracle is a high-performance Data Warehouse that can be used for Analytics and Machine Learning purposes. This Data Warehouse is extremely secure and features a robust multi-tenant architecture.

2) Amazon Web Services – Redshift

Amazon Web Services – Redshift is a Cloud-based, fully-managed Data Warehouse that enables users to connect with a variety of data sources and BI tools. It provides both serverless (preview) and provisioned services, allowing users to conduct analytics without worrying about managing the Data Warehouse. 

3) BigQuery

BigQuery is a multi-cloud, serverless and highly scalable Data Warehouse specifically built for business agility. Using BigQuery, you can get real-time updates on different types of business operations. BigQuery also comes along with built-in tools like Machine Learning, Geospatial Analysis, and Business Intelligence to enable users to efficiently manage and analyze the data.

4) Snowflake 

Snowflake is a popular Cloud Data Warehouse built on top of AWS or Azure and Googe cloud architecture. It is known for its ability to accommodate multi-cloud architecture configurations. Snowflake also helps with Data Integration, Business Intelligence, Security, and Advanced Analytics. Snowflake’s architecture is what sets it apart from other Data Warehouses. The architecture is designed to allow independent scaling of storage and computation.

What is Tableau?

Tableau Data Warehouse: Tableau logo
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Stanford researchers Pat Hanrahan, Christian Chabot, and Chris Stolte founded Tableau in January 2003. Tableau was acquired by Salesforce later in 2019. The headquarters of the corporation is now in Seattle, Washington.

Today, Tableau is known as one of the popular Interactive Data Visualization platforms that mainly focuses on Business Intelligence (BI). Tableau allows for complex computations, Data Blending, and Dashboarding in order to create appealing visualizations.

Tableau aids in the simplification of raw data into a format that is simple to comprehend. With Tableau, Data Analysis can be performed faster, and the visualizations can be generated in the form of Worksheets and Dashboards.

Tableau Software Products

Following are some of the Tableau products: 

  • Tableau Desktop
  • Tableau Online
  • Tableau Mobile
  • Tableau Public
  • Tableau CRM
  • Tableau Prep

According to the convenience, users can choose the products. In this article, we see how to install the Tableau Desktop product.

Install Tableau Desktop 

  • Step 2: On the screen, as shown below, click on the “TRY NOW” button in the upper right corner.
Tableau Data Warehouse: Install Step 2
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  • Step 3: On clicking the button, it will redirect to the following screen. You now have to enter the email address, and then press the “DOWNLOAD FREE TRIAL” button.
Tableau Data Warehouse: Install Step 3
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  • Step 4: This will start downloading the Tableau Desktop. Now, open the downloaded file, accept the agreement and click on the “Install” button. 
Tableau Data Warehouse: Install Step 4
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  • Step 5: Now that the installation is completed, you can open the Tableau Desktop application. The following screen will appear.
Tableau Data Warehouse: Install Step 5
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Understanding the value of Business Intelligence (BI) & Warehousing

Now, let us understand what Business Intelligence is and what is the value of BI and Warehousing together in organizations today.

What is Business Intelligence?

Business Intelligence (BI) dates back to the 1800s, when financial counselors exploited market knowledge that their competitors lacked to gain an advantage. It was in 1989 when Howard Dresner, a former Gartner analyst, coined the term Business Intelligence. BI refers to a group of intelligent systems that collect, organize, analyze, and display proprietary data to enable users to derive business insights. 

Importance of BI

The goal of Business Intelligence is to use relevant data to improve a company’s operations. Organizations that use BI tools can turn their acquired data into useful information about their organizational operations and plans. Such information can then be utilized to make better decisions that boost productivity and revenue, resulting in faster growth and profitability.

What is the value of Business Intelligence and Warehousing together?

Business Intelligence is a collection of Applications, Tools, and infrastructure that enables organizations or users to optimize their Business Decisions and Performance. And a Data Warehouse is the storage and organization of that data to support BI operations. Today, maintaining and deploying a Data Warehouse is so crucial to BI that it is commonly referred to as BIDW. BIDW has been helping organizations in more than one aspect. Some of them are explained below.

1) Performance Metrics

Metrics are used to evaluate the activities and behavior of a business, as well as its overall performance. Additionally, Performance Metrics define a range of the data that can be used to construct, confirm, or refute a hypothesis based on previously established business objectives. 

2) Democratize Data

Data Democratization is based on the self-service approach, which enables everyone in the organization to have easy access to the data. This approach allows users to utilize desired data without the need for permission from administrators. Democratizing the data using BIDW provides users the flexibility to instantly access and comprehend data, resulting in faster decision-making. 

3) Data Storytelling

Translating Data Analysis into layman’s words in order to influence a strategic business decision is known as Data Storytelling. The right warehouse for the data and Business Intelligence tools makes it quicker to collect data, compile information, and share stories.

4) Data Mining

Data Mining, also known as knowledge discovery, is a method of extracting useable data from a larger quantity of raw data. This method aids in the discovery of trends, themes, and patterns in enormous volumes of data. In BI, data mining techniques are frequently employed to categorize, group, predict and correlate different aspects of businesses.

Methods to Connect Tableau Data Warehouses

Method 1: Connecting Tableau Data Warehouses using Tableau Driver

Tableau’s in-built Data Warehouse connector conveniently establishes a connection with Oracle. You can easily set up a data source and use Tableau to visualize your data to perform a fruitful analysis for your business. This method requires you to install the Tableau Oracle driver.

Method 2: Automated Process Using Hevo to Connect Tableau Data Warehouses

Use Hevo, A No-Code Data Integration Platform to connect Oracle with various other marketing applications to bring in integrated data in a matter of minutes and visualize it in your desired BI tool such as Tableau that too without writing a single line of code. Its fault-tolerant architecture ensures that the data is handled in a secure, consistent manner with zero data loss.

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Methods to Connect Tableau Data Warehouses

In this section, you will learn how to connect to Tableau Data Warehouse(Oracle).

Method 1: Connecting Tableau Data Warehouses using Tableau Driver

Install Oracle Tableau Driver 

For connecting to Tableau Data Warehouse(Oracle), you will need to install the Oracle Tableau Driver first.

Tableau Data Warehouse: Tableau Driver Step 1
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  • Step 2: Install the Driver version of your choice.
Tableau Data Warehouse: Tableau Driver Step 2
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Similarly, you can install the driver for the rest of the Tableau Data Warehouses. Go to the Tableau Driver and install the driver of your choice. 

Steps to Connect Oracle to Tableau

  • Step 1: Once you have installed Tableau on your system, on the right-side pane as shown below, click on Oracle or ‘More…’ and then click on Oracle.
Tableau Data Warehouse: Connect Step 1
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  • Step 2: Now, Enter the server name. Next, choose between Integrated Authentication and a specific user name and password. When connecting to an SSL server, tick the Require SSL box.
Tableau Data Warehouse: Connect Step 2
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  • Step 3: Select OK. Now, the Tableau Data Warehouse(Oracle).

Method 2: Automated Process Using Hevo to Connect Tableau Data Warehouses

Source: Self

Hevo Data, a No-code Data Pipeline helps you directly transfer data from Data Warehouses and Databases like Oracle and 100+ other data sources (including 40+free data sources) such as Tableau, Data Warehouses, or a destination of your choice in a completely hassle-free & automated manner. Hevo allows you to move data to the desired data destination. You can also connect Data Warehouses like Google BigQuery as a source, you check out Hevo’s official document here.

Hevo is fully managed and completely automates the process of not only loading data from your desired source but also enriching the data and transforming it into an analysis-ready form without having to write a single line of code. It provides a consistent & reliable solution to manage data in real-time and always have analysis-ready data in your desired destination. 

Steps to use Hevo

Hevo focuses on three simple steps to get you started:

  1. Connect: Connect Hevo with Data Warehouses or Database like Oracle and various other sales & marketing data sources by simply logging in with your credentials.
  2. Visualize: Connect Hevo with your desired BI tool such as Tableau and visualize your unified marketing data easily to gain better insights

More Reasons to Choose Hevo Data

  • Fully Managed: It requires no maintenance as Hevo is a fully automated platform.
  • Data Transformation: It provides a simple interface to perfect, modify, and enrich the data you want to transfer. 
  • Fault-Tolerant: Hevo is capable of detecting anomalies in the incoming data and informs you instantly. All the affected rows are kept aside for correction so that it doesn’t hamper your workflow.
  • Real-Time: Hevo offers real-time data migration. So, your data is always ready for analysis.
  • Schema Management: Hevo can automatically detect the schema of the incoming data and maps it to the destination schema.
  • Live Monitoring: Advanced monitoring gives you a one-stop view to watch all the activities that occur within pipelines.
  • Live Support: Hevo team is available round the clock to extend exceptional support to its customers through chat, email, and support calls.
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Conclusion

When it comes to making the best, most timely decisions for your organization, having a good relationship with your data is essential. Tableau Data Warehouse can help you accomplish these goals by integrating a robust Data Warehouse with Business Intelligence best practices. However, it is also important to represent the processed data in a way that is comprehensible and visually appealing. In case you want to export data from a source of your choice such as Tableau into your desired Database/destination then Hevo Data is the right choice for you! 

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Hevo Data, a No-code Data Pipeline provides you with a consistent and reliable solution to manage data transfer between a variety of sources like Tableau and a wide variety of Desired Destinations, with a few clicks. Hevo Data with its strong integration with 100+ sources (including 40+ free sources) allows you to not only export data from your desired data sources & load it to the destination of your choice, but also transform & enrich your data to make it analysis-ready so that you can focus on your key business needs and perform insightful analysis using BI tools.

Want to take Hevo for a spin? Sign Up for a 14-day free trial and experience the feature-rich Hevo suite first hand. You can also have a look at the unbeatable pricing that will help you choose the right plan for your business needs.

Share your experience of learning about the Tableau Data Warehouse! Let us know in the comments section below!

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