Our Approach: Agile Data Science

Unleash your data’s business potential – now.

Most enterprises want to get going with predictive data science, but need help identifying analytics that will quickly add value to their businesses.

Once they do, they quickly come to realize that Data Science is not a project, it’s a way to do business. That’s why TROVE developed its Agile Data Science approach, a four-step, collaborative-learning methodology that helps clients identify the right opportunities for prediction, put their data to work, and get to meaningful results fast – all without the pain of having to buy a multi-million-dollar data science platform purchase with no ROI in sight.

“The Agile Data Science process was a game changer for us. Even though we were busy hiring data scientists, we were running into problems pointing them in the right direction. TROVE solved that.” 

– Large Mid-Atlantic Utility

Agile Data Science Delivers Value Quickly

Agile Data Science is a collaborative-learning approach that gets clients to results quickly using TROVE’s advanced Solver technology and data science team, the Science Squad®. Agile Data Science not only streamlines the predictive data science process, it provides focus, learning, accountability, and buy in, which help ensure the results of the process are implementable. Agile Data Science is not a ‘project-based’ approach; instead, it is a way for clients to apply predictive analytics holistically to their businesses by tackling specific, high value use cases.

The four steps of Agile Data Science:

STEP 1:
Develop the Concept

This step is about determining the right opportunities to tackle with predictive data science. The TROVE Science Squad® and Product Team meet with the client to hone in on opportunities that matter, then do broad-stroke thinking to make sure there is a path forward to fulfilling it.

STEP 2:
Workshop the Concept

In this step, the TROVE team works with the client to dig into the data to see what’s there and what isn’t, and how it is generated and gathered, ultimately making sure the data assets and means of getting to them are clearly mapped out. Working with subject matter experts and the business owner within the client, the team teases out the nuance of the opportunity and calculates how success will be measured.

STEP 3:
Prove the Concept

In this key step, the Science Squad® develops the solution for a logical subset of the client’s business using actual client data and AI models. The Science Squad organizes and enhances the client’s data, models it, and then applies the appropriate Solver, demonstrating its capabilities and tuning the output so that the result is actionable with validated learnings and an ROI.

STEP 4:
Operationalize the Concept

Here, clients interested in extending the impact of their successful Proof of Concept engage the TROVE team to deploy Solvers at enterprise scale, address priority data gaps, automate data feeds and partner on the plan to fully implement the solution. 

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