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Data Warehouse in Tableau | Everything You Need to Know

Last updated on 28th Jan 2023, Artciles, Blog

About author

Pramoot Prakash (AWS Cloud Architect )

Pramoot Prakash is an AWS Cloud Architect Senior Manager and has 8+ years of experience in controlling cloud-based information and being a cloud architect inside the process of making hardware and software recommendations, handling audit logs, and running AWS Cloud trials.

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    • In this article you will learn:
    • 1.What are Data Warehouses?
    • 2.Various Data Warehouses.
    • 3.What is Tableau?
    • 4.Tableau Software Products.
    • 5.Install Tableau Desktop.
    • 6.Methods to a Connect Tableau Data Warehouses.
    • 7.Conclusion.

What are Data Warehouses?

The term ‘Data Warehousing’ was coined by an IBM researchers Barry Devlin and Paul Murphy in a late 1980s. The purpose of a data warehousing approach was to build the architectural model for moving data from an operational systems to decision environments. Data Warehouse is the Data Management system that enables and supports a Business Intelligence (BI) particularly analytics operations. Data Warehouses provide an organizations with the broad and unique benefit of allowing them to analyse a massive volumes of data. The four unique characteristics of a Data warehouses are:

Integrated: Data Warehouses bring together various types of data from a various sources to establish consistency.

Subject-Oriented: Data Warehouses can aid in the analysis of data relevant to a certain functional area.

Time-Variant: Data Warehouse helps to in examining a changes over time.

Non-Volatile: The data that enters a Data Warehouse remains non-volatile.

Various Data Warehouses:

1. Oracle:

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

2. Amazon Web Services – Redshift:

Amazon Web Services – Redshift is a cloud-based fully-managed data warehouse that allows customers to connect to a range of data sources and business intelligence applications. It offers both serverless (preview) and provided services allowing customers to do analytics without having to bother about managing the Data Warehouse.

3. BigQuery:

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

4. Snowflake :

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

Components of Data Warehouse Architecture

What is Tableau?

Tableau was developed in January 2003 by Stanford scholars Pat Hanrahan, Christian Chabot and Chris Stolte. Later in 2019 Tableau was bought by Salesforce. A corporation’s headquarters are currently in Seattle Washington.Today Tableau is known as one of the famous Interactive Data Visualization platforms that mainly focuses on a Business Intelligence (BI). Tableau allows for a complex computations, Data Blending and Dashboarding in order to create a appealing visualizations.Tableau aids in a simplification of raw data into a format that is a simple to comprehend. With Tableau Data Analysis can be a performed faster and also visualizations can be generated in a form of a Worksheets and Dashboards.

Tableau Software Products:

Following are some of a Tableau products:

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

Install Tableau Desktop :

Step 1: Go to the Tableau Desktop and install a latest version of Tableau.

Step 2: On a screen as shown below click on a “TRY NOW” button in upper right corner.

Step 3: On clicking a button it will redirect to a following screen now have to enter an email address and then press a “DOWNLOAD FREE TRIAL” button.

Step 4: This will start downloading a Tableau Desktop. Now open a downloaded file accept a agreement and click on the “Install” button.

Step 5: Now that an installation is completed and can open a Tableau Desktop application.

Methods to a Connect Tableau Data Warehouses:

Method 1: Using a Tableau Driver to connect two Tableau Data Warehouses.

Method 2: Process Automation Connecting Tableau Data Warehouses with a Hevo.

Method 1: Using Tableau Driver to Connect Tableau Data Warehouses

Install Oracle Tableau Driver For connecting to a Tableau Data Warehouse(Oracle) will need to install a Oracle Tableau Driver first.

Step 1: Go to a Tableau Driver. Select Oracle.

Step 2: Install a Driver version of your choice.

Similarly can install a driver for the rest of a Tableau Data Warehouse. Go to Tableau Driver and install the driver of the choice.

Steps to Connect Oracle to Tableau:

Step 1: Once you have installed a Tableau on the system on the right-side pane click on an Oracle or ‘More…’ and then click on Oracle.

Step 2: Now Enter a server name. Next choose between the Integrated Authentication and a specific username and password. When connecting to the SSL server tick a Require SSL box.

Step 3: Select OK. Now Tableau Data Warehouse(Oracle).

Tableau Architecture

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

Steps to use Hevo focuses on a three simple steps to get be started:

Connect: Log in with credentials to connect Hevo to Data Warehouses or Databases such as Oracle and several other sales and marketing data sources.

Visualize: Connect Hevo with a desired BI tool like Tableau and visualize a unified marketing data easily to gain a better insights.

More Reasons to Choose Hevo Data:

Fully Managed: It needs no maintenance as a Hevo is a fully automated platform.

Data Transformation: It provides the simple interface to perfect, modify and enrich a data want to transfer.

Fault-Tolerant: Hevo is capable of detecting anomalies in incoming data and informs instantly. All the affected rows are kept aside for a correction so that it doesn’t hamper a workflow.

Real-Time: Hevo offers a real-time data migration. So the data is always ready for an analysis.

Schema Management: Hevo can automatically detect a schema of incoming data and maps it to a destination schema.

Live Monitoring: Advanced monitoring gives a one-stop view to watch all activities that occur within pipelines.

Live Support: Hevo team is available round a clock to extend exceptional support to its customers through chat email and support calls.

Conclusion:

When it comes to making best most timely decisions for an organization having a good relationship with data is essential. Tableau Data Warehouse can help to accomplish these goals by integrating the robust Data Warehouse with Business Intelligence best practices. However it is also important to represent processed data in a way that is comprehensible and visually appealing.

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