Recent technology advancements are poised to significantly impact the way in which data scientists and data analysts work.
In 2023, six trends have the potential to accelerate machine learning (ML) and move organizations from descriptive and diagnostic analytics that focus on what happened and why, toward predictive and prescriptive analytics that instead forecast what will happen and provide powerful insights on how to change the future.
In this ebook, you will learn how:
- Unified infrastructure supporting multiple programming languages is allowing data scientists, data engineers, and data analysts to leverage the maximum potential of each
- Feature stores enable data scientists to manage and deploy ML features at scale by delivering reproducibility, discoverability, and scalability
- Data analysts and scientists are increasingly able to utilize the power of systems once reserved for ML engineers in order to facilitate and participate in more efficient production processes
- Increasingly accessible web app development in Python is empowering data scientists to make their models more comprehensible and actionable
- Rapid advancements in open source libraries, tools, and frameworks demonstrate the need for a solution that prepares data science and ML investments for the future