Building a high-performance data and AI organization
Among the companies in our survey, 63% use cloud services or infrastructure widely in their data architecture
There are 14 sectors represented in the sample, and all respondents work in organizations earning $1 billion or more in annual revenue.
Every organization recognizes the strategic value of generating actionable insights from their enterprise data. That’s why data-driven companies are deploying increasingly advanced cloud-based technologies, including analytics tools with machine learning capabilities — but they’re still hamstrung by a lack of abundant, easily accessible, high-quality data.
How are organizations grappling with this dilemma? This MIT Technology Review Insights report summarizes the findings from a global survey of more than 350 CDOs, CIOs and other data and analytics leaders from companies such as CVS, Estée Lauder, Hivery, McDonald’s and Northwestern Mutual.
Download now to get valuable insights such as:
- Why only 13% of organizations are currently delivering on their data strategy (and what these leaders credit their success to)
- Why data leaders prioritize the democratization of analytics and machine learning
- Why over half of respondents said they’re struggling to scale ML use cases
- Why open standards are the primary requirement for future data architecture strategies