New research shows overconfidence about AI could lead to a higher risk of failure and costly mistakes amounting to hundreds of millions of dollars.

Enterprises have complex IT and technology needs. To reach business goals, organizations must often stitch together a patchwork of software and IT systems. So, it’s understandable that the thought of adding yet another technology—low-code—might cause trepidation. But low-code excels at integrating seamlessly with any technology. Low-code tools speed up development work and enable rapid application development.

Hakkoda’s 2024 State of Data report found misalignment between data leaders on AI readiness.

Why forward-thinking organizations are turning to a data mesh architecture.

Data lakes can save your enterprise money but come with unique challenges. These tips will help you overcome three of the biggest issues.

Exploring fraud detection with automated data integration in a cloud data warehouse: part two of two.

Learn how CHS Inc., a Fortune 500 secondary cooperative, leverages Fivetran, Snowflake and dbt to improve supply chain efficiency and power its billion-dollar operation.

Why data lakes are the essential centerpiece of modern data architectures and an indispensable prerequisite for AI.

This marks an incredible three-peat win, solidifying our ongoing commitment to innovation and collaboration within the Google Cloud ecosystem.

Today’s business environment depends on collecting and analyzing a broad range of data. Data integration, therefore, has become critical when consolidating diverse data types. Without data integration, you’re left with siloed information that’s very difficult—if not impossible—to analyze. Comma-separated values play a fundamental role in data integration, especially when you need to join tables that share column names or want to move datasets between analytical tools.