Data Management | News, how-tos, features, reviews, and videos
Once you get your retrieval-augmented generation system working effectively, you may face new challenges in scalability, user experience, and operational overhead.
With digital maps and vast databases, there’s no limit to how rich and real-time maps can get. Accuracy and consistency will come from a system of unique identifiers called GERS.
The tools provide advanced data intelligence, data quality, and data modeling capabilities aimed at helping customers ensure the AI readiness of their data, the company said.
Pinecone is a managed, cloud-native vector database offering long-term memory for high-performance AI applications.
Data pipelines are essential for connecting data across systems and platforms. Here's a deep dive into how data pipelines are implemented, what they're used for, and how they're evolving with genAI.
Enterprises have largely favored the same programming languages and databases for the past decade, so don’t panic if you haven’t mastered artificial intelligence yet.
The extract, transform, and load phases of ETL typically involve multiple tasks, each of which can be executed independently. This means you can develop each task as a microservice.
A modern AI-enabled iPaaS solution that supports collaborative workflow design and management can break down silos between IT and business teams and propel automation initiatives forward.
A headless data architecture means no longer having to coordinate multiple copies of data and being free to use whatever processing or query engine is most suitable for the job. Here’s how it works.
The enhancements to cloud databases are expected to help in the development of AI-based and real-time applications.