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Modernizing data with strategic purpose

In partnership with MIT Technology Review Insights

As organizations strive to adopt AI and other data-driven emerging technologies, many are held back by the same persistent foundational challenges — data quality and availability, governance issues and legacy architecture complexity.


In response, leaders are taking steps to modernize their data capabilities, re-assessing their strategies, and setting up new processes, systems and practices to solve their biggest underlying challenges once and for all. 


Thoughtworks recently collaborated with MIT Technology Review Insights to find out how 350 data leaders across a variety of industries are approaching their data modernization journeys – key themes explored included key objectives of modernization and potential benefits, developing a vision and strategy, common impediments and how to address them, and gaining organizational alignment and business buy-in.


Get your copy to explore the findings, along with advice from data modernization experts and in-depth overviews of data modernization initiatives at three large organizations.

46% of data and tech executives

say that better decision-making is the primary aim of their data modernization efforts — ranking it above supporting AI models (40%) and decarbonization (38%).

Download your copy to discover why you must:

Keep your AI goals in perspective and consider the broader value that delivering higher quality data faster and more securely can create for your business.

Align modernization objectives to wider strategic objectives, and clearly articulate how data can help business units achieve their objectives to secure critical buy-in.

Bring modern software engineering practices to your data strategy and apply them to solve persistent challenges around data quality, access and usability.

Explore the full report

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