How Will Automation Tools Change Data Science?
Data science is now a major area of technology investment, given its impact on:
- customer experience,
- revenue,
- operations,
- supply chain,
- risk management, and
- multiple other business functions.
Data science enables a data-centric decision-making process for organizations. It is accelerating digital transformation and AI initiatives. According to Gartner, Inc. only 4 percent of CIOs have implemented AI, and only 46 percent have plans to do so.
While investments continue to grow, many enterprises find it increasingly challenging to implement and accelerate data science practices. This article provides an overview of recent trends in machine learning and data science automation tools. It also addresses how those tools will change data science.
Read the full article “How Will Automation Tools Change Data Science” on KDnuggets, featuring Dr. Ryohei Fujimaki, CEO and founder of dotData.
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 dotdata.com, and join us on Twitter and LinkedIn.
