Data science has evolved dramatically over the last 10 years. However, very few organizations have experienced the full business impact or competitive advantage from their advanced analytics, despite significant investments in data science and machine learning (ML). The reason? Many of the tools needed to scale ML are too complicated, and necessary skill sets are in short supply. But change is now afoot. Technology advancements in 2021 will significantly impact the way in which data scientists and data analysts work. In 2021, six trends have the potential to accelerate ML and move organizations from descriptive and diagnostic analytics (explaining what happened and why) towards predictive and prescriptive analytics that forecast what will happen and also provide powerful pointers on how to change the future.

In this ebook, you will learn how:

• Easy-to-use ML tools and consolidated data platforms empower data analysts and bridge the gap between analytics and ML
• Snowflake’s Data Cloud can expand data access and data sharing through a secure ecosystem with access to ready-to-use third-party data
• Data engineering tools remove the burden of data prep for data scientists and make repurposing existing work easy
• New distributed training frameworks offer an alternative superior to Spark while delivering up to 2,000x faster performance
• Rapid advancements in ML libraries, tools, and frameworks demonstrate the need for a solution that future-proofs data science and ML investments