CAMBRIDGE, Mass., June 10, 2024 -- A new report by MIT Technology Review Insights, produced in partnership with Databricks and dbt Labs, uncovers key shifts in data engineering, the evolving skill set required of data practitioners, options for data infrastructure and tooling to support AI, and data challenges and opportunities emerging in parallel with generative AI.

Insights (PRNewsfoto/MIT Technology Review Insights)

This report is being debuted as part of the Databricks Data + AI summit in San Francisco this week. The theme of this event is how data intelligence enables every organization to harness the power of GenAI on its own data.

The report, "The data practitioner for the AI era," is based on a series of interviews with executives and data leaders. Among the organizations represented are Apixio, Tibber, Fabuwood, Starship Technologies, StockX, Databricks, and dbt Labs.

The findings are as follows:

  • The foundational importance of data is creating new demands on data practitioners. As the rise of AI demonstrates the business importance of data more clearly than ever, data practitioners are encountering new data challenges—as well as establishing newfound organizational importance.



  • Data practitioners are getting closer to the business, and the business closer to the data. The pressure to create value from data has led executives to invest more substantially in data-related functions. Data practitioners are being asked to expand their knowledge of the business—while functional teams are finding they require their own internal data expertise to leverage their data.



  • The data and AI strategy has become a key part of the business strategy. Business leaders need to invest in their data and AI strategy—including making important decisions about the data team's organizational structure, data platform and architecture, and data governance—because every business's key differentiator will increasingly be its data.



  • Data practitioners will shape how generative AI is deployed in the enterprise. The key considerations for generative AI deployment are the province of data engineers, giving them outsize influence on how this powerful technology will be put to work.

"The reality is that what data engineers do lays the foundation for AI. It's absolutely necessary, and they have the power to make or break all of these AI applications," says Reynold Xin, cofounder and chief architect, Databricks.

"In the current AI-driven landscape, data practitioners shape the future of the enterprise—with their expertise in high demand," says Laurel Ruma, global director of custom content for MIT Technology Review. "The connection between data practitioners and business outcomes underscores critical decision points for unlocking the full potential of data and AI strategy. As generative AI evolves, data practitioners hold significant influence in transforming the enterprise."

To download the report, click here.

Visit dbt at booth 91

For more information please contact:

Natasha Conteh

Head of Communications

MIT Technology Review Insights

natasha.conteh@technologyreview.com

About MIT Technology Review Insights

MIT Technology Review Insights is the custom publishing division of MIT Technology Review, the world's longest-running technology magazine, backed by the world's foremost technology institution—producing live events and research on the leading technology and business challenges of the day. Insights conducts qualitative and quantitative research and analysis in the U.S. and abroad and publishes a wide variety of content, including articles, reports, infographics, videos, and podcasts. And through its growing MIT Technology Review Global Insights Panel, Insights has unparalleled access to senior-level executives, innovators, and entrepreneurs worldwide for surveys and in-depth interviews.

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