Data integration technologies and practices, including data pipelines, ETL/ELT, and APIs, are essential to supplying users and applications with trusted data at the right time for reports, dashboards, ...

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 ...

As organizations evolve their data infrastructures to support modernization efforts, they are often dealing with multiple engines and data repositories, including cloud data warehouses and data lakes ...

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 ...

Enterprises are under increasing pressure to ensure the health and integrity of their data as they work to support data products, analytics, and applications. To stay ahead, they must face the ...

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 ...

Are you ready to remove data silos quickly and create unique customer profiles for accurate segmentation? The latest white paper from Ventana Research reveals how you can achieve these goals and more.

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 ...

Mark Madsen, president of Third Nature and TDWI faculty member, joins host Andrew Miller to discuss real-time data integration - including defining "real-time", which technologies organizations are ...

To harness data’s full potential, organizations must ensure the integrity, availability, and efficiency of their data processes. They need to be able to track and observe the data flowing through ...