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Data doesn’t just magically appear in the right place for enterprise analytics or AI, it has to be prepared and directed with data pipelines. That’s the domain of data engineering and it has long been one of the most thankless and tedious tasks that enterprises need to deal with.
Today, Google Cloud is taking direct aim at the tedium of data preparation with the launch of a series of AI agents. The new agents span the entire data lifecycle. The Data Engineering Agent in BigQuery automates complex pipeline creation through natural language commands. A Data Science Agent transforms notebooks into intelligent workspaces that can autonomously perform machine learning workflows. The enhanced Conversational Analytics Agent now includes a Code Interpreter that handles advanced Python analytics for business users.
“When I think about who is doing data engineering today, it’s not just engineers, data analysts, data scientists, every data persona complains about how hard it is to find data, how hard it is to wrangle data, how hard it is to get access to high quality data,”Yasmeen Ahmad, managing director, data cloud at Google Cloud, told VentureBeat. “Most of the workflows that we hear about from our users are 80% mired in those toilsome jobs around data wrangling, data, engineering and getting to good quality data they can work with.”
Targeting the data preparation bottleneck
Google built the Data Engineering Agent in BigQuery to cre …