Maana’s “Knowledge First” Approach

Hear Maana Founder, President and CTO, Donald Thompson talk about Maana’s “Knowledge First” approach and how Maana’s Computational Knowledge Graph helps form and answer the problem questions.



We designed the system with three goals in mind: One is interoperability to make sure that you could take advantage of the existing systems and services and algorithms you’ve already developed. Two is reusability so that from project to project you get acceleration from being able to take advantage of what you’ve already invested in. Third we enable more people to participate in the development of these solutions using visual programming, low code, no code techniques, the subject matter experts, the data scientists, and the analysts can all work together collaboratively to deliver these solutions at scale. At the heart of a Maana solution is what we call the computational knowledge graph it’s what enables us to take the subject matter expertise and frame it in the form of problem questions which are then solved by both data and algorithms coming together. Traditionally, data analytics involves starting with the data and doing a bottom-up approach. With knowledge, we take a more human approach. We focus first on the subject matter experts and how they think about the problem. This is involving concepts, the relationships between those concepts, as well as the types of operations we need to perform in order to solve the business problems. So knowledge involves trying to answer the business problem from a top-down perspective. The ‘knowledge first approach’ encourages creating reusable components, and those reusable components can access existing services, they can access third-party services, or internal services that you’ve already developed. Unlike other platforms, Maana doesn’t require you to move all of your data or algorithms into a new system. Instead we can take advantage of where data already resides, as well as the algorithms and systems we’ve already developed. Maana’s interactive development environment promotes iterative collaboration across the entire team, developing solutions from the analysts to the architects to the data scientists to the engineers. The visual modeling environment enables subject-matter experts and analysts to work together in order to test the solution as it’s being developed. Based on years of working with some of the world’s largest companies on solving some of their hardest problems, we’ve really designed the platform to address the needs of delivering these kinds of solutions at scale. This includes making sure that the systems and services and the people that are in these companies can easily adopt these new technologies, enabling subject matter experts to really participate in the interactive development of these solutions.



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