Remove solutions unified-storage
article thumbnail

Exploring real-time streaming for generative AI Applications

AWS Big Data

Another example is an AI-driven observability and monitoring solution where FMs monitor real-time internal metrics of a system and produces alerts. For example, in a chatbot, data events could pertain to an inventory of flights and hotels or price changes that are constantly ingested to a streaming storage engine.

article thumbnail

Multicloud data lake analytics with Amazon Athena

AWS Big Data

With a unified query interface, you can avoid the complexity of managing multiple query tools and gain a holistic view of your data assets regardless of where the data assets reside. Solution overview Imagine a fictional company named Oktank, which manages its data across data lakes on Amazon S3, ADLS, and GCS.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

What does AI think is a good analogy for a Business Data Fabric?

Timo Elliott

Similarly, a data fabric is a unified data infrastructure that connects and integrates various data sources, storage systems, and processing technologies within an organization. What would be a compelling title for a marketing presentation talking about a business data fabric solution? Do you have other creative examples?

article thumbnail

Petabyte-scale log analytics with Amazon S3, Amazon OpenSearch Service, and Amazon OpenSearch Ingestion

AWS Big Data

You can also migrate data between different storage tiers. Hot storage is used for indexing and updating, and provides the fastest access to data. Hot storage takes the form of an instance store or Amazon Elastic Block Store (Amazon EBS) volumes attached to each node.

Data Lake 111
article thumbnail

DataOps Enables Your Data Fabric

DataKitchen

Tools vendors are creating their own definitions of “data fabric” to promote their own product and solution offerings. If you search the Internet for a definition of data fabrics you can see discussions of storage, AI augmentation, and other tools.

article thumbnail

Product lifecycle management for data-driven organizations 

IBM Big Data Hub

When each business unit or product team manages their own data, product data can overlap with the other unit’s data causing several issues, such as duplication, manual remediation, inconsistent pricing, unnecessary data storage and an inability to use data insights.

article thumbnail

Unleashing the potential: 7 ways to optimize Infrastructure for AI workloads 

IBM Big Data Hub

Cloud platforms and container orchestration technologies provide scalable, elastic resources that dynamically allocate compute, storage and networking resources based on workload requirements. Leveraging distributed storage and processing frameworks such as Apache Hadoop, Spark or Dask accelerates data ingestion, transformation and analysis.