Setting realistic expectations and taking lessons from previous tech trends can help you plan for successful AI programs.

Data quality management is a high priority in most modern organizations. It enables enterprises to ensure that their data remains accurate, consistent, compliant, and otherwise trustworthy for all ...

A comprehensive 2.5-day summit designed for data and business leaders, focusing on how organizations can evolve their strategies to support generative AI. Developing a modern data and analytics ...

Many organizations are planning applications for generative AI, but for AI to be successful, the organization’s data must be trustworthy. As organizations continue their journey to generative AI, new ...

TDWI research indicates that a growing number of companies are collecting 100s of terabytes and petabytes of data. This includes structured data as well as text data, machine data, image data, and a ...

Generative AI is transforming the way enterprise data scientists extract insights from data and deliver these insights to business teams. To accelerate analytics endeavors, data science teams are ...

Sophisticated AI applications are at the heart of modern business go-to-market strategies. When deployed into customer-facing applications, AI can power better sales performance, more effective ...

The digital business era, driven by artificial intelligence (AI) and generative AI (gen AI), demands unified, interoperable data to overcome challenges like data integrity and control concerns. IDC’s ...

If you have an older, traditional MDM system, it may be holding you back now. Not only do these systems often lack the scalability and performance needed for today’s massive data volumes, but they ...

With high-quality, timely data for your business intelligence and AI/ML initiatives, you can improve business efficiency, mitigate risks, enhance the customer experience, and improve insights for ...