The democratisation of data and insights: Expanding machine learning access
Published on 17th November 2020 by InterEx Group
In the second instalment of this series, Google Cloud’s Director of Product Management, Data Analytics, Sudhir Hasbe, and Google Cloud Product Manager Ryan Lippert, discuss why artificial intelligence (AI) and machine learning (ML) are critical to generating insights in today’s world of big data. A report by McKinsey highlights just how crucial AI and ML are to success: by 2030, companies that fully integrate AI could double their cash flow, while companies that don’t could see a 20% decline.
While ML and AI have long been seen as the domain of experts with PhDs, Google Cloud is democratising ML by building a suite of cutting-edge tools for data analysts, developers, and data engineers. For data analysts, Google Cloud has brought ML inside the data warehouse with BigQuery ML. For developers, they offer a set of pre-trained models that are easily accessible by APIs, as well as AutoML custom models, which are suitable for models that require more specificity. Finally, Google Cloud have democratised ML for data engineers in both buckets of data engineering: the Dataproc-oriented open source path, and the cloud-native Dataflow path.
Read the full article from Google Cloud here.
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