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Data across organizations is growing and that organizations need a very strong analytics platform to leverage this data create insights and make real-time decisions on top of this data.
That’s driving the advent of three large trends. First is the convergence of data lakes and data warehouses, that’s enable organizations to maximize the value of their data.
Second, is the growing phenomena of real-time decision-making which is forcing enterprises to think of how they can support the needs of batch processing and streaming data.
Finally, there is the rise of artificial intelligence and machine learning, which allows enterprises to leverage their data and create competitive differentiation.
With this background, Sudhir Hasbe, Director of Product Management, Data Analytics, Google Cloud, walks us through Google Cloud’s smart analytics offerings—and what’s new.
He takes us on a tour through the technical value of Google Cloud’s smart analytics platform end-to-end. He provides a comprehensive overview and demos what’s new and what’s next in Google Cloud’s smart analytics portfolio across products like BigQuery, Dataflow, Dataproc, Data Fusion, PubSub, Data Catalog, Dataprep, and Looker.
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As organizations continue to produce vast quantities of data, they increasingly need platforms that allow them to analyze, store, and extract meaningful insights from that data. And research from analyst firms like Gartner offer an important way for organizations to evaluate and compare cloud data warehouse providers. Earlier this year,
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