AI-Powered Data Transformation

Modern data environments present significant challenges to data engineering productivity. Legacy tooling fails to meet the demands of today's distributed, diverse, and dynamic data landscapes, leading to poor data intelligence and limited discovery and governance. Also, hybrid and multi-cloud architectures increase the complexity of data processes, demanding both code-free and code-friendly solutions for data teams.

IDC's latest analyst brief highlights AI-powered data transformation as a solution to these challenges. These modern tools offer intelligent copilots, low-code interfaces, and code-friendly environments, supporting open standards and DevOps practices. By empowering users of all skill levels, these solutions help organizations improve metrics, streamline data management, and navigate complex data landscapes effectively.

This analyst brief provides invaluable insights into:

• What stands in the way of data engineering productivity in today's modern data environments
• Limitations of legacy offerings and the complexity of managing multiple technologies 
• How the lack of data intelligence and insufficient tooling impacts data discovery and governance
• Benefits of AI-powered data transformation tools including intelligent copilots and considerations for selecting the right tools for your organization