Tableau + AWS: Accelerating your digital transformation with Modern Cloud Analytics

Updated December 4, 2019: At AWS re:Invent, we announced that Tableau Server achieved the Amazon Redshift Ready designation, part of the Amazon Web Services (AWS) Service Ready Program. Tableau is excited for this designation as an AWS Partner Network (APN) member with a successful integration with Amazon Redshift that is both generally available and fully supported for AWS customers.

Analytics and cloud technologies are two critical components in helping organizations along their digital transformation journeys. But digital transformation doesn't happen overnight. The reality for most businesses is that data comes in faster than IT can curate it. This generates more migration to the cloud to take advantage of flexibility, agility, and easier access to information, but businesses need to be able to analyze all kinds of data—from unstructured to fully prepared data—at all times on this journey.

Partnering with AWS to offer powerful analytics in the cloud

To help customers throughout their modernization journeys, Tableau is continuously investing in stronger, joint solutions with cloud partners, like Amazon Web Services (AWS). Earlier this year, we introduced the Tableau Server Management Add-on—at launch, customers with AWS can choose to host their Tableau Server metadata repository externally with Amazon Relational Database Service (RDS) for increased scalability, and they can centralize key management efforts to unlock advanced security and compliance scenarios through Amazon Key Management Services (KMS).

At Tableau Conference 2019, we also announced an expansion of our partnership with AWS, launching the Modern Cloud Analytics initiative (MCA). This initiative helps customers unlock the power and flexibility of self-service analytics in the cloud and accelerate their transition to a modern analytics platform. Having a comprehensive technology stack in the cloud can support the data integration, self-service analytics, and use cases that businesses need to digitally transform and achieve analytics at scale.

A diagram showing data flows through AWS cloud services integrated with Tableau analytics

Tableau integrates with AWS services to provide a powerful end-to-end cloud analytics platform.

The benefits of cloud migration for data and analytics

According to TDWI research, companies are capturing terabytes of data from dozens or more sources, and in a self-service manner, to drive insight and action. Although, this doesn’t mean that they’ve modernized their data warehouse and analytics architecture. A single-layer analytics solution in a modern stack can help you overcome some of the pitfalls of using a traditional analytics solution or on-premises data warehouse, including data silos, stagnant data, redundant work efforts, and limited visibility into business health. And Tableau can be that analytics solution—with connections to diverse data sources regardless of the data type or structure, anywhere you’re at in your cloud migration.

Modernizing your analytics environment can be done in many ways, but TDWI’s Checklist Report also provides a useful reference with six keys to success in the modern data warehouse and analytics stack. To ensure that you can use data, no matter how much there is, there are critical elements and functionality to have in your cloud-friendly data architecture, according to TDWI. Let’s look at a few.

  • A cloud data warehouse — There’s growing interest in cloud data warehouses for data management to support comprehensive analytics. By adopting a cloud data warehouse such as Amazon Redshift, you get the necessary storage, compute, and security resources for big data workloads, and minimal setup, maintenance, or cost is required. In fact, users typically appreciate the “pay-as-you-go” model so that cost incurred matches use. It also supports multiple data types (e.g., semistructured, unstructured, and structured), and varying analytic processes or formats to simplify data ingestion, transformation, and consumption.
  • Cloud-based, self-service analytics — More companies have embraced platforms that provide self-service data discovery and offer advanced, predictive analytics. A “one-size-fits-all” approach to business intelligence doesn’t suffice because everyone falls differently on the cloud and analytics spectrum. However, flexible, visual analytics can support different needs, user skill sets, and business requirements—whether you’re technically inclined or not. By connecting Tableau to your cloud warehouse (e.g., Amazon Redshift) and other providers that make up your modern data architecture, you can manage, process and get value from all data, driving insight and action to solve business problems.

Finally, as you prioritize and check the features of your technology stack, don’t forget to ask and answer these questions. With this assessment, you’ll find there are important capabilities, some of which are noted below.

  • How many data sources do we have?
  • Will our data tools handle all of the sources?
  • What analytics are valued across the organization?
  • Are advanced analytics needed, now or in the future?
  • Are all security and governance requirements met?

Must-have capabilities include:

  • Governance — These are clear processes, standards, and measures that support secure management of your data. Governance must anchor your architecture to create an environment where data is trusted and certified.
  • Strong alliances — When vendors can bring the power of a partner network to their engagement with you, you’ll receive a full suite of products and technical services that integrate with one another.
  • Cost efficiency — No one wants to pay for what they don’t need or use. Think big picture as you build your technology stack so that you settle on a suitable cost and pricing structure that matches individual and enterprise use.

Learn more about Modern Cloud Analytics

Did you miss us at AWS re:Invent this year? You can still learn more about Modern Cloud Analytics—we've brought together the power of Tableau, AWS, and our joint partner ecosystem to help you maximize the value of your data and analytics investments and support your end-to-end analytics journey.

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