News
10 Big Data Trends You Should Know About For 2022
Rick Whiting
From predictive analytics and data fabric architecture to data observability and data governance software, here’s a look at 10 big data trends and technologies that solution and service providers need to be aware of in the new year.
Increased Deployment And Large-Scale Use Of Machine Learning
Machine learning has been a hot area in the last few years with both established IT vendors and – especially – startups offering software for developing, training, deploying and managing machine learning models and the data they use. This year will see the use of ML tools become more widespread due to several developments, according to a report from Snowflake on data science and analytics trends.
Easy-to-use machine learning tools, including “AutoML” or automated machine learning software, will automate the technical aspects of data science tasks. That will allow data scientists to do their jobs more quickly and even make data science capabilities available to a wider audience of data analysts.
Managing and deploying machine learning features at scale will become easier with increased use of feature store technology that has become available in the last year, according to the report. And continuous releases of machine learning tools, libraries and frameworks offer more options for data scientists.
Machine learning projects will increasingly be housed in cloud data platforms such as Snowflake and Databricks, predicts Eckerson Group.
And some see machine learning and data analytics essentially merging into one operation. “Automation, business intelligence and AI will converge into one practice, fueling the proliferation of citizen data scientists across the enterprise,” said Florian Douetteau, co-founder and CEO of Dataiku, an AI and machine learning platform developer, in an email.
