In the early days of software development, applications were built to run on a single, compatible, physical machine. With the introduction of VMware in the 1990s, developers embraced the ability to run their applications on virtual machines that could then run on any physical machine architecture. And with the turn of the new millennium, cloud computing made its debut. Developers are no longer constrained to a physical machine’s architecture, running their applications entirely on the cloud. Cloud platforms allow you to build applications that easily scale up or down based on demand.

As we enter the next decade of trends in cloud computing, the value of running applications in the cloud will increasingly hinge on a new and important consideration: cloud-agnostic. Simply put, the term cloud-agnostic refers to the ability to move applications or parts of applications from one cloud platform to another.

But what does cloud-agnostic have to do with your chosen BI platform? What does it mean for your data? Let’s dive into what you should consider in a BI platform to ensure you’re protecting and future-proofing your company’s data strategy. 

You Should be Able to Run Your BI Platform On Any Cloud 

Your BI platform is an application like any other. Deploying applications within containers on a cloud platform allows development teams to optimize resource utilization and leverage best-of-breed capabilities from multiple vendors simultaneously. And for your company, avoiding vendor lock-in drives down the cost of running and managing your BI. 

A cloud-agnostic BI platform won’t confine your developers to a single cloud architecture — because that’s not how magic is made. It should be built on a portable, containerized microservices architecture that gives you the flexibility to leverage the best functionalities of any available cloud architecture and the freedom to dynamically orchestrate microservices as your BI projects expand. Portability should also extend beyond public clouds to support private clouds and on-prem architectures simultaneously.

Further, your BI platform should enable your developers to create analytic apps for internal teams and customers that allow flexibility with no lock-in and the ability to store those apps wherever it’s most functional and cost-efficient. 

You Should be Able to Store Your Data In Any Cloud

Just as you wouldn’t want to be locked into an architecture for running your BI platform, you don’t want to be locked into where you can store your data either. Once your BI platform is running where you want it to run, it must have access to your data wherever it lives. And you need a BI platform built to connect to any data source and multiple data sources simultaneously, whether public clouds, private clouds, or even legacy on-prem architectures.

This functionality is especially pertinent in the case of mergers and acquisitions — you want to ensure your BI platform can support any future architecture that your company inherits along the way. As markets consolidate and acquisitions are made, incorporating multiple data architectures shouldn’t necessitate the consolidation of new data sources and data models with a single cloud vendor. Your BI platform should enable complete agility as your company grows and evolves, without the limitations of a single data-model or cloud architecture to achieve actionable insights. 

Look for a Cloud-Agnostic Product Roadmap

The business intelligence and cloud computing markets experience consolidation like any other. When considering a BI platform for your organization, it’s therefore critical that a vendor’s product roadmap emphasizes future investments in cloud-agnostic capabilities. Being cloud-agnostic today doesn’t guarantee a focus on cloud-agnostic product development in the future. And if you’re building a data strategy that depends on the flexibility of a cloud-agnostic BI platform and access to multiple data sources, you want to ensure that your data strategy is future-proof. 

We’ve already seen stratification in this space. When Google acquired Alooma, the ETL provider quietly dropped support for their Redshift connector, a direct competitor of Google BigQuery. Moves like these are great for the acquiring company’s bottom line. But they come at the cost of true consumer flexibility — and your company’s ability to confidently invest in a cloud-agnostic data strategy. Ensure that your BI platform has a well-documented history of investments in cloud-agnostic capabilities and a robust roadmap to update and expand these capabilities as the market evolves. 


The more that you can commoditize the compute infrastructure, the more flexibility you have to move around your analytic apps and your data for price or best-of-breed functionality. 

As a cloud consumer, flexibility in where you store your data and analytic apps is a priority for your data teams, your developers, and your company’s financial bottom line. The ability to execute a truly flexible, cloud-agnostic data strategy, however, is contingent on how much the platforms you use to manage your data value their customers’ flexibility. Before you pull the trigger on a BI platform, make sure that platform has your back.

Scott Castle is the VP of Strategy at Sisense. He brings over 25 years of experience in software development and product management at leading technology companies including Adobe, Electric Cloud, and FileNet. Scott is a prolific writer and speaker on all things data, appearing at events like the Gartner Enterprise Data Conference, Data Champions, and Strata Data NYC.

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