Seagate® Technology Holdings plc (NASDAQ: STX), a world leader in mass-data storage infrastructure solutions, announced the launch of Lyve™ Cloud Analytics platform, a complete cloud-based analytics solution that includes storage, compute, and analytics, to help Lyve Cloud customers lower the total cost of ownership (TCO) and accelerate time to value with their DataOps and MLOps (machine learning operations).
Seagate Launches Lyve Cloud Analytics Platform to Optimize Machine Learning Operations and Accelerate Innovation
October 12, 2022 by
Unstruk Data: Empowering Enterprises to Transform Unstructured Data Files into Actionable Intelligence about Real-world Assets and Locations
May 31, 2022 by
The latest version of Unstruk’s flagship product is the first commercially available DataOps platform built to generate intelligence about real-world assets and locations, so that it can be utilized to automate processes, inform business decisions or integrate into other critical workflow systems.
DataOps Dilemma: Survey Reveals Gap in the Data Supply Chain
September 22, 2021 by
The survey associated with this report, commission by Immuta, focused on identifying the limiting factors in the data “supply chain” as it relates to the overall DataOps methodology of the organization. DataOps itself is the more agile and automated application of data management techniques to advance data-driven outcomes, while the data supply chain represents the technological steps and human-involved processes supporting the flow of data through the organization, from its source, through transformation and integration, all the way to the point of consumption or analysis.
DataOps Dilemma: Survey Reveals Gap in the Data Supply Chain
September 20, 2021 by Leave a Comment
The survey associated with this report, commission by Immuta, focused on identifying the limiting factors in the data “supply chain” as it relates to the overall DataOps methodology of the organization. DataOps itself is the more agile and automated application of data management techniques to advance data-driven outcomes, while the data supply chain represents the technological steps and human-involved processes supporting the flow of data through the organization, from its source, through transformation and integration, all the way to the point of consumption or analysis.
Video Highlights: Unleashing DataOps Keynote
April 4, 2021 by
In this keynote presentation from the DataOps Unleashed virtual conference, innovator Kunal Agarwal, CEO of Unravel Data, describes how companies large and small are using DataOps to make their technology stacks hum, get more done at a lower cost, and improve both customer experience and the bottom line.
Data Engineering Survey: 2021 Impact Report
February 3, 2021 by
This Data Engineering Survey: 2021 Impact Report summarizes key findings from the inaugural survey and provides a glimpse into the current and future state of data engineering and DataOps. The report highlights some of the major trends uncovered in this year’s survey including the adoption of cloud data platforms, what platforms are winning (and emerging), what data engineers find to be their biggest challenges, and how organizations are handling sensitive data.
Data Engineering Survey: 2021 Impact Report
February 1, 2021 by Leave a Comment
This Data Engineering Survey: 2021 Impact Report summarizes key findings from the inaugural survey and provides a glimpse into the current and future state of data engineering and DataOps. The report highlights some of the major trends uncovered in this year’s survey including the adoption of cloud data platforms, what platforms are winning (and emerging), what data engineers find to be their biggest challenges, and how organizations are handling sensitive data.
DataOps Engineer Will Be the Sexiest Job in Analytics
September 17, 2020 by
In this contributed article, Christopher Bergh, a Founder and Head Chef at DataKitchen, discusses how DataOps, is transforming the roles on the data analytics team. DataOps is a better way to develop and deliver analytics. It applies Agile development, DevOps and lean manufacturing principles to data analytics producing a transformation in data-driven decision making.
Model Risk Management in the Age of AI
June 30, 2020 by
In this contributed article, Stu Bailey, Co-Founder and Chief AI Architect of ModelOp, discusses how financial services companies can easily validate multiple AI/ML models and reduce ML project costs by 30% through automation. ModelOps refers to the process of enabling data scientists, data engineers, and IT operations teams to collaborate and scale models across an organization. This drives business value by getting models into production faster and with greater visibility, accountability and control.
