There is a movement underway with enterprises shifting to run on algorithms instead of processes, according to Forrester principal analyst Michele Goetz. She recently gave a keynote in New York at the Denodo DataFest conference on data virtualization for the cloud, machine learning, and analytics. Goetz shared with the audience her perspective that posits the escalation of automation is pushing the current “data fabric” to its limits with a new frontier ahead.
“Stop building monolithic systems,” she said, despite fears organizations might have of business disruption. Goetz said organizations still using such legacy systems should plan a step-by-step migration process to a more nimble archtecture. From her vantage, a convergence of data virtualization, APIs, and microservices could help enterprises become more agile and adaptable.
“We are living in a world where we all aspire to be insight driven,” she said. Goetz explained that means the world is filled not only with structured data in databases but other sources such as documents, medical images, and video surveillance. Understanding and using data regardless of its format can be achieved, she said, through such tools as smartphones and wearable devices.
With data coming from diverse sources, more consideration should be given to alternate ways of handling it beyond automated spaces, databases, and applications. “We need it to run at the edge because that’s where it’s personal and creates the most value,” Goetz said. “It has to adapt. How many of you want to spin dials and widgets to get your data to work?”
Intelligence may be embedded everywhere within an information ecosystem, she said. In a sense, Goetz said, it means organizations are living with artificial intelligence and not just trying it out. Furthermore, she said enterprises are already on the path of seeing their businesses visualized within the data -- looking at spreadsheets is just the start. Now organizations want data to be as tangible to the business as it is experienced in reality, to the point of moving into simulations. “The next-generation information fabric is hitting upon all of those areas to bring that new world to life,” Goetz said.
There is a greater role for algorithms to play, she said, from supporting information systems to the edge. As analytics and machine learning capabilities advance, algorithmic models are being deployed in different areas, Goetz said. Organizations could find value, she said, from such insights. In what she described as a many-to-many relationship, there can be an escalation of data connections where sets of information from one or more resources connect to many others, and so on. “In the future, our next-gen information fabric has to manage and maintain an ecosystem of algorithms working together that also exponentially defines our business experiences and customer value,” she said.
One of the goals, Goetz said, is to be more responsive in real time to events but to also be more predictive and optimize the handling and maintaining resources. Smartphones can be put to work in the field to help with that, she said, thanks to their built-in tools such as cameras and GPS that can capture and upload data. There can be smart algorithms for data collection that can feed into predictive analytic capabilities for managing resources and assets, she said. “That is seeing your business in data,” Goetz said. “That requires an information fabric that supports that many-to-many relationship.”
There comes a point where data is viewed as a product, she said, that should not just be locked way. Business stakeholders might assume value comes from apps, Goetz said, but data is necessary to fuel those apps. “You really want to be thinking about how you’re bringing that data up into the tiers where the APIs to execute the services and experiences will be,” she said. That will be one of the first things to change, Goetz said, as organizations consider how they architect data services and APIs.
Taking advantage of data virtualization investments, she said, is part of making the most of forward-looking plans organizations may have. “Data always operates on the edge,” Goetz said. “You have to be there too. Your next-gen fabric architecture and investment needs to put you there.”