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Product lifecycle management for data-driven organizations 

IBM Big Data Hub

In a world where every company is now a technology company, all enterprises must become well-versed in managing their digital products to remain competitive. In other words, they need a robust digital product lifecycle management (PLM) strategy. In addition, there is a downstream team that owns product transactional data.

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IBM doubles down on hybrid cloud with $6.4B HashiCorp acquisition

CIO Business Intelligence

In the statement , the company said HashiCorp’s suite of products offers “enterprises with extensive Infrastructure Lifecycle Management and Security Lifecycle Management capabilities,” which enable businesses to automate their hybrid and multicloud environments.

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erwin and Snowflake Partnership: Helping Our Customers Manage and Govern the Entire Data Lifecycle

erwin

Our customers are in search of creative and sustainable ways to increase their speed to insights for digital transformation, infrastructure modernization and cloud migration and many of them are looking to implement the Snowflake Cloud Data Platform. Well, we think so. Let me know your thoughts on the new erwin/Snowflake partnership.

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Whether your technology is new or old, lifecycle management is key

CIO Business Intelligence

However, in an increasingly software-centric environment, both new and legacy assets must deliver value throughout their lifecycle. Business needs first, then the lifecycle management program Your infrastructure lifecycle management program should be aligned with your organization’s growth roadmap.

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MLOps 101: The Foundation for Your AI Strategy

Machine Learning Operations (MLOps) allows organizations to alleviate many of the issues on the path to AI with ROI by providing a technological backbone for managing the machine learning lifecycle through automation and scalability. Download this comprehensive guide to learn: What is MLOps? Why do AI-driven organizations need it?

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What IT leaders need to know about the EU AI Act

CIO Business Intelligence

The law will create new mandates for organizations to validate, monitor, and audit the entire AI lifecycle, says Kjell Carlsson, head of AI strategy at Domino Data Lab, a data science and AI company. The transparency and monitoring requirements will be a new experience for some organizations, Domino Data Lab’s Carlsson says.

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Climate and Sustainability Hackathon—Meet the Judges!

Cloudera

The Hackathon was intended to provide data science experts with access to Cloudera machine learning to develop their own Accelerated Machine Learning Project (AMP) focused on solving one of the many environmental challenges facing the world today.

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Use It, Save It, Or Lose It: Spring Cleaning for Information Governance

Speaker: Speakers Michelle Kirk of Georgia Pacific, Darla White of Sanofi, & Scott McVeigh of Onna

Spring has sprung, which means it’s time to get your data house in order. As an organization’s most valuable asset, data should be cared for and integrated, managed, archived, and deleted as appropriate. Watch this webinar on-demand to learn about: Data lifecycle management.

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Democratizing AI for All: Transforming Your Operating Model to Support AI Adoption

Democratization puts AI into the hands of non-data scientists and makes artificial intelligence accessible to every area of an organization. Brought to you by Data Robot. Aligning AI to your business objectives. Identifying good use cases. Building trust in AI. Key questions for executives and leaders to answer about their AI strategy.