We're on the verge of a perfect storm for modern data access governance. As organizations lean into data and the cloud, new research shows that the majority will adopt multiple cloud compute technologies within the next two years. As a result, data teams will need a modern framework, architecture, and suite of tools to make their cloud data platforms work together efficiently and securely.

This report highlights the current and future state of data engineering and DataOps, including analysis on:

• The adoption rate of cloud data platforms and what is means for the future of data use
• The most challenging aspects of the cloud data management process
• Handling sensitive data in an increasingly regulated environment
• What organizations and data teams need to remain competitive in our evolving data ecosystem

When it comes to the enterprise, data science and data governance programs are built on competing objectives, and enterprises have no choice but to try to satisfy both demands. Compliance and privacy programs, for example, require increasingly strict limitations on who can use what data and why, thanks to increasing regulations on data. On the other hand, data scientists need access to as much data as possible, as quickly as possible — otherwise their analysis could fall flat.

Our founding team spent over a decade working in the U.S. Intelligence Community, tackling some of the most complex and sensitive data problems in the world. This paper outlines lessons we've learned about how data science and governance programs can, if implemented properly, reinforce each other's objectives, and in the process, strengthen the core goals of your business and maintain customer loyalty.

Within the next two years, 75% of organizations expect to be "primarily" or "entirely" cloud-based, and more than half plan to adopt two or more cloud data platforms. This shift is not necessarily unexpected — but it is happening faster than industry analysts predicted. This white paper dives deep into the future of cloud data ecosystems to uncover:

• How the rise of DataOps and cloud data access are forcing data teams to evolve
• The biggest obstacles facing data teams as they adopt multiple cloud data platforms
• The limitations of traditional data protection processes and why they can't scale across cloud platforms
• How the increasing use and regulation of sensitive data could hinder its value and impact
• Specific ways data teams can overcome these challenges, as demonstrated by The Center for New Data