Data ProDUCT vs Project

Top 5 Reasons Why your Data Science Project Didn't Make it and How to Get It Right the First Time

Strategic Plan you Need to get your Data Product into Production


Every Data Scientist is hired to bring value to the business and is expected to develop and iterate on data products that help the company grow. But not every data analytics project is a data product. This talk, based on 25+ collaborations with companies of all industries and sizes, will cover 5 of the most common reasons for what’s necessary to upgrade your data analytics project into a data product. You will learn:

  • How to better collaborate with your stakeholders

  • What to ask before the project begins

  • What to watch out for as you’re developing data products

  • What software requirements you should be aware of

  • What resources you need to have

By the end of the session, the audience will have a better understanding of the technical and organizational considerations for iterating on data initiatives, and walk away with practical advice for how to help your company get return on data investment and make it more data-driven.



  • Data products

  • Machine Learning in Production

You may also like: