Tableau is one of the popular tools for data visualization, allowing users to create interactive dashboards and reports utilizing various data sources. That’s not all; you require a strong analytics infrastructure that can manage data and deliver excellent performance. But what is Amazon Web Services or AWS? It is none other than a cloud computing platform that provides tools and services to improve your performance. If you keep reading this article further, you can learn all about the best practices to improve your tableau on AWS.
Resizable compute power is available in the cloud through a web service called Amazon Elastic Compute Cloud (EC2). When running on AWS, choosing the suitable EC2 instance is essential based on the quantity and complexity of your data. You can find different specifications and shapes of EC2 instances. Some of them include CPU, memory, storage, and network speed. For example, an Elastic Compute Cloud instance that has more CPU cores and memory will be better suited or appropriate for tasks requiring a lot of data. You can make sure that Tableau has enough computing power to handle massive data sets and complex calculations by selecting the appropriate instance.
You may store and access data online with a scalable object storage service like an Amazon Simple Storage Service (S3). Using Amazon S3 for data storage allows for the efficient management of massive amounts of data. You can store it effectively, inexpensively, and safely while maintaining top performance. Additionally, you may combine or integrate Tableau and Amazon S3 together. You will have simple access to your data thanks to this collaboration or integration instead of laborious data warehousing.
You may store and analyze massive data sets with the fully managed, petabyte-scale data warehouse service called Amazon Redshift. And optimizing the performance becomes effortless when you offload data processing and storage to the cloud. Additionally, you can easily scale your data up or down depending on your needs, ensuring you have enough processing power to handle large data sets. Not only that, but Amazon Redshift and tableau on aws are interoperable or compatible with each other.
This functionality enables you to automatically alter your computing resources in accordance with the demands of your applications. Additionally, you can guarantee that your apps have the required processing power to handle the workload. For instance, you may automatically scale up your EC2 instances during peak hours to handle any workload and scale them down during off-peak hours to save money. Your Tableau workloads will always be accessible even during unanticipated traffic spikes, thanks to auto-scaling.
You can share file systems across several instances with the help of EFS or Amazon Elastic File System, a scalable and fully managed file storage service. In addition, make sure that your Tableau workloads have access to shared file storage by allowing you to collaborate and share data. Since it is an economical option, you can effortlessly get rid of the requirement for complicated file-sharing systems like NFS (Network File System).
In conclusion, utilizing AWS’s capabilities can significantly improve Tableau’s performance and effectiveness. By adhering to the abovementioned best practices, you may build a strong and scalable analytics infrastructure to acquire deeper insights into your data.