Information Builders today announced it is making its analytics software available via Docker containers that can be employed to facilitate the movement of analytics between platforms or create “sandboxes” on public clouds through which additional compute resources can be invoked dynamically.
Announced at the annual Information Builders Summit conference, the company also unfurled a managed instance of its data management and analytics software available on Amazon Web Services (AWS).
Information Builders also revealed it is making available a set of tools for curating data specifically for artificial intelligence (AI) applications, an updated version of its WebFOCUS data visualization tools and support for the open source Kafka messaging platform.
Jake Freivald, vice president of marketing for Information Builders, says the company will support organizations that want to deploy the company’s software on any public cloud. However, when it comes to customers who want Information Builders to manage that cloud environment on their behalf, the company will require those customers to use AWS.
Information Builders has decided to embrace Docker containers along with Kubernetes container orchestration software as a means to enable cloud bursting with an analytics application as well as provide a way to make it easier for organizations to distribute analytics, Freivald says. The company also envisions the containerized analytics will be employed to drive real-time processes using the Kafka messaging platform, he adds.
Information Builders is at the front end of what will become a larger analytics race to embrace Docker containers. Because containers make it easier to run application code on multiple platforms, analysts will be able to create analytics that can be distributed more easily and embedded programmatically with a variety of business processes.
It will be up to each organization to determine to what degree they want to be able to build and support containerized applications. Information Builders, via its alliance with AWS, is signaling that as data management continues to become increasingly complex more organizations will prefer to rely on a vendor to manage their business intelligence (BI) application environment. Thanks to the support for Docker containers, many organizations also will have the option of pursuing a hybrid approach that relies on containers to enable additional compute capacity to be dynamically invoked on a public cloud.
It may take a while for analysts and developers who support them to master that capability. However, the pressure to infuse more analytics into business processes is building. Organizations want to be able to embed both predictive and prescriptive analytics into a wide variety of digital business processes. The challenge they face is that as those processes continue to evolve, organizations also need to be able to dynamically update the analytics modules embedded within those processes.
The biggest challenge, however, may come down to educating analytics and business leaders on what can be achieved by embracing Docker containers. Several decades worth of treating analytics as a batch process that needs to run on a data warehouse has created a level of inertia concerning the state of what possible using advanced analytics that will be challenging to overcome.