Data API and GraphQL leader Hasura announced significant innovations that enable unified access to distributed data, governed by a central semantic and authorization framework. This solves one of the hardest problems facing businesses building AI features and products: connecting their LLM models to enterprise data, composed from multiple domains, while complying with governance and security policies.
Faster AI and HPC Workflows with Quobyte’s New File Query Engine
July 12, 2024 by
[SPONSORED GUEST ARTICLE] What sets Quobyte’s File Query Engine apart is its integration with the file system’s distributed metadata architecture. Unlike solutions that require separate database layers, Quobyte’s engine operates ….
Quobyte Software-Defined Storage Brings Its HPC and Hyperscaler Heritage to AI Workloads
June 13, 2024 by
Quobyte comes from an HPC heritage as well as providing storage solutions for hyperscalers. “We wanted to bring HPC to the enterprise with the software approach that made the ….
Ocient Releases the Ocient Hyperscale Data Warehouse version 20 to Optimize Log and Network Metadata Analysis
July 26, 2022 by
Ocient, a leading hyperscale data analytics solutions company serving organizations that derive value from analyzing trillions of data records in interactive time, released version 20 of the Ocient Hyperscale Data Warehouse. New features and optimizations include a suite of indexes, native complex data types, and the creation of data pipelines at scale to enable faster and more secure analysis of log and network data for multi-petabyte workloads.
Facial Recognition, Video Analytics, Geospatial and Other AI Techniques Aiding Ukraine’s Investigations of Russian War Crimes
April 12, 2022 by
…. investigators in Ukraine are engaged in the grim task of gathering evidence for possible war crime trials of Russian soldiers. For that, the investigators are aided by advanced machine learning technology, including facial recognition, geospatial data analytics, image analysis and analysis of streaming video from security cameras.
What Data Governance Means to Cloud Computing (And Vice Versa)
July 16, 2021 by
In this contributed article, editorial consultant Jelani Harper points out that the symbiosis between data governance and cloud computing is apparent to any organization with significant cloud investments. The cloud has a plethora of resources that enhance data governance, which is critical for regulatory compliance, risk mitigation, and long term profitability of data assets.
Beyond Discoverability: Metadata to Drive Your Data Management
February 5, 2020 by
Terrell Russell from iRODS gave this talk at SC19. “The Integrated Rule-Oriented Data System (iRODS) is open source data management software used by research organizations and government agencies worldwide. iRODS is released as a production-level distribution aimed at deployment in mission critical environments. It virtualizes data storage resources, so users can take control of their data, regardless of where and on what device the data is stored.”
Panel Discussion: Metadata and Archiving at Scale
April 14, 2019 by
In this video from the HPC User Forum, Henry Newman from Seagate Government Solutions leads a panel discussion on Metadata and Archiving at Scale. “Metadata is the key to keeping track of all this unstructured scientific data. It is “data about data.” It makes scientific data easy to find, track, share, move and manage – at low cost. Unfortunately, today’s high capacity storage systems only provide bare bones system consisting of as little as file name, owner and creation/access timestamps. Data intensive scientific workflows need supplemental enhanced metadata, along with access rights and security safeguards.”
No More Scampering for Data
April 6, 2018 by
In this contributed article, Sanat Pai Raikar, Senior Manager at Tredence, discusses how the metadata phenomenon plays up in an Organization. A metadata-based approach will enable organizations to work with all their data assets within the same environment. It provides a consistent definition, establishes relations and traceability back to the origin of the data set in question.
