The Top 5 AI & Machine Learning Trends for 2021 And Beyond

How and Why Your Enterprise Should Democratize Data Science

February 7, 2019

Data science is now a major area of technology investment given its business impact.  Business impact may be realized via:

  1. customer experience,
  2. revenue,
  3. operations,
  4. supply chain,
  5. risk management, and
  6. multiple other business functions.

However, recent research indicates that although digital transformation and AI journeys are key initiatives, companies are struggling to get them off the ground.  One of the key challenges is hiring the right team including a scarce commodity — the data scientist.
One of the most noticeable trends to overcome this challenge, and to accelerate enterprise data science is data science democratization.  This process would empower citizen data scientists (such as business analysts and business intelligence engineers) to solve complex analytic problems, making it possible for a broader range of practitioners to execute data science projects.  Although this concept has been widely discussed, many enterprises have been struggling to truly democratize data science. This article discusses best practices for enterprises to follow when democratizing data science.

Read the full article “How and Why Your Enterprise Should Democratize Data Science” in TDWI, featuring Ryohei Fujimaki, dotData CEO and founder.


dotData Inc.

dotData Automated Feature Engineering powers our full-cycle data science automation platform to help enterprise organizations accelerate ML and AI projects and deliver more business value by automating the hardest part of the data science and AI process – feature engineering and operationalization. Learn more at, and join us on Twitter and LinkedIn.