Cisco Introduces Data Fabric to Integrate Machine Data for Enhanced AI Insights
Cisco has announced the launch of the Cisco Data Fabric, an innovative architecture designed to help organisations process machine data for artificial intelligence applications. This new platform aims to alleviate the complexities and costs associated with managing large volumes of machine data, enabling companies to leverage this data for AI model training, automated workflows, and operational analysis. Jeetu Patel, President and Chief Product Officer at Cisco, emphasised that organisations are sitting on a wealth of machine data that has previously been too challenging to utilise effectively. The Data Fabric, built on the Splunk platform acquired by Cisco, seeks to unify machine data from various enterprise IT and operational environments, including networks, servers, applications, and physical sensors.
The capabilities of the Cisco Data Fabric include advanced data filtering, shaping, and tiering, along with federated analytics that integrate insights from multiple data sources. Cisco highlights that intelligent edge data management facilitates near real-time operational intelligence, while an AI-driven experience layer reduces manual overhead and accelerates decision-making. The platform is designed to operate on machine data at what Cisco refers to as “extreme scale,” supporting transformations across edge, cloud, and on-premises environments. It allows for real-time searching and analysis of data from cloud data lakes and traditional storage systems, with current support for Amazon S3 and future plans for integration with Apache Iceberg, Delta Lake, Snowflake, and Microsoft Azure. The Data Fabric is described as flexible and compatible with open industry standards, enabling deployments in both private and public environments.
Categories: Data Fabric, Machine Data Management, AI Integration
Tags: Data Fabric, Machine Data, Artificial Intelligence, AI Model Training, Operational Intelligence, Data Integration, Real-Time Analysis, Cloud Environments, Edge Computing, Data Management