How to Build a Data Science Roadmap and Choose Best Data Science Projects

Webinar by ganes kesari on best way to choose data science projects
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Building a robust data science roadmap is a critical step in the process of achieving data science maturity. A data science roadmap helps organizations focus on getting maximum value out of data. Business leader start mapping ROI with their data science efforts and data is gradually integrated with the organizational culture.

In this article, we summarize how to build a data science roadmap and how to choose the best data science projects based on it.

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How to Get RoI from the Data Science projects

Gartner says that almost 80% of analytics projects in enterprises fail. The reasons could be many, right from lack of data literacy across the organization to lack of skills and focus to solve real-world problems.

All these problems point out to one major insufficiency in technology organizations – ranking low in the levels of data maturity

Gartner predicts that by 2022, 90% of organizational strategies will explicitly mention information as a critical enterprise asset and analytics as an essential competency.


Organizations across the globe are competing for a finite number of data science resources – Data Scientists, analysts, analytical tools, data pools, etc. – without measuring the parameters of success and failure.

The extent of a successful data science project cannot be achieved if the leadership hasn’t formulated the strategy or questions that data science needs to answer or paved the route to production.

Even after investing millions in integrating the complete data infrastructure, it’s not easy to get RoI from the Data Science projects. Results with the rate and accuracy leaders are demanding once the system is in production, get elusive.

Problems with Data Science projects. Comic created using ComicGen by Gramener.
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Problems with Data Science projects

Why is it Difficult to Get Business Value from Data Science projects?

There could be numerous reasons hidden in plain sight – undefined goals and business processes, inappropriate data infrastructure, and failure to differentiate between academic research and the real world. 

That’s why Gramener organized a webinar to help you build a successful data science roadmap and get RoI from your analytics engagements.

Ganes Kesari was live for an expert session on 14th November 2019 at 10:00 AM EST. He spoke about how to get maximum business value from Data Science projects. He used many business use cases and Gramener case studies to deeply discuss the value of data science projects.

Ganes is the Co-founder and Chief Decision Scientist at Gramener and leading successful data science teams for almost a decade. Ganes is a thought leader and an international speaker. He has delivered multiple talks at renowned platforms such as TEDx, and O’Reilly summits.

How to Build a Successful Data Science Roadmap | Webinar by Ganes Kesari

The above video is a recorded version of the 45-minute webinar. Ganes used industry examples, to explain a simple step-by-step approach to unlock business value. Find it all in the link below. Know what it takes to convince and onboard your technology and business teams for the next best project.

Throughout the webinar you will learn

  • A crash course on data science advisory and your position in data maturity stages
  • Key reasons why data science projects fail
  • How to identify your projects and prioritize them
  • A 3-step framework for building your data science roadmap
  • The approach illustrated with real-world case studies
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5 thoughts on “How to Build a Data Science Roadmap and Choose Best Data Science Projects”

  1. Data Science Training in Hyderabad

    Thanks for the nice blog. It was very useful to me. I’m happy I found this blog

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