Data insights are a critical component of data analysis. It helps you make sense of complex data and communicate your findings effectively. Tableau, a business intelligence and data analyzing tool, connects you to various data sources and creates interactive and insightful visualizations. This article will discuss using tableau on aws to create compelling analytics and insights.
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Business Intelligence on AWS
Tableau is a powerful data insight tool that requires computing resources to handle large datasets and complex calculations. AWS provides a scalable and secure cloud infrastructure that can handle these requirements. By running AWS with Tableau, you can leverage the cloud’s scalability and flexibility to analyze and visualize data at any scale.
There are two ways to use the tool. You can install the Server on an EC2 instance or use Amazon QuickSight, a fully-managed business intelligence service that integrates with Tableau. Let’s take a look at both options.
Server on EC2
Tableau Server is a self-hosted enterprise-level platform. Installing the server on an EC2 instance allows you to leverage AWS’s scalability, security, and flexibility to create and manage your intelligence environment. It requires more maintenance and management than Amazon QuickSight.
Amazon QuickSight is another business intelligence service that Amazon Web Services (AWS) offers.QuickSight provides a fully-managed cloud service that eliminates the need for infrastructure setup and maintenance, making it a cost-effective solution for small and large businesses.
- Connecting QuickSight to AWS Data Sources
It integrates with various data sources, including AWS services such as Amazon Redshift, Amazon RDS, and Amazon S3, as well as third-party data sources.
Amazon QuickSight is more accessible and requires less management than Servers on EC2. However, it provides less control over your environment and may not be suitable for complex and large-scale insights.
- Connecting to AWS Data Sources
Whatever option you choose, connecting Tableau to your data sources on AWS is essential for creating insightful analysis. It can connect to various AWS data sources, including Amazon Redshift, Amazon RDS, Amazon S3, and Amazon Athena.
Visualising Data in Intelligence
Tableau provides a variety of chart types and analysis options to help you explore and communicate your data effectively. They are mentioned below.
Choose the right chart type: It provides over 20 chart types, including bar charts, line charts, scatter plots, and heat maps. Choose the chart type that best represents your data and insights.
- Use color and shape to encode data: In your analytics, colour and shape can encode additional data dimensions. For example, you can use color to represent different categories or shape to differentiate between data points.
- Add interactivity: This allows you to create interactive data reports by adding filters, actions, and tooltips. This allows your audience to explore and analyze your data in more detail.
- Tell a story with your data: Use your data to tell a story and communicate your insights effectively. Add titles, captions, and annotations to guide your audience through your analysis.
Sharing Your Visualisations
Once you have created your visualizations you can share them with others in various ways.
- Publish to Tableau Server: If you use Server on EC2, you can publish your analytics to the server and share them with others in your organization. You can control access and permissions to ensure authorized users can view and interact with your data.
- Export as an image or PDF: You can export your data visuals as an image or PDF and share them via email or other communication channels. This allows you to share your insights with a broader audience, even if they cannot access the intelligence platform.
- Embed in a webpage: It provides an option to embed in a webpage using an iframe. This allows you to integrate visualizations into your website or other web-based applications.
Tableau is a powerful data analytics tool and using it on AWS provides the scalability and flexibility needed to analyze and visualize large datasets. Whether you install the intelligence platform on the Server on EC2 or use Amazon QuickSight, connecting them with AWS data sources is essential for creating insightful data. By following best practices for data visualization you can communicate your insights and make data-driven decisions.