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DataOps vs. DevOps: What’s the Difference?

Alation

DataOps and DevOps are two distinctly different pursuits. Both are based on agile frameworks that are designed to accelerate working cycles. But where DevOps focuses on product development, DataOps aims to reduce the time from data need to data success. What is DevOps? What is DataOps? And so it goes.

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SolaaS: Your gateway to streamlined success

Dataconomy

What is Solution as a Service (SolaaS)? This scalability feature enables businesses to remain agile and responsive to market changes without incurring substantial costs. An innovative use of cloud computing, “Solution as a Service” involves the delivery of an entire IT solution rather than its individual components.

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Connected products at the edge

IBM Journey to AI blog

For more information about the concept, see the link below. For more information about the concept, see the link below. There are many overlapping business usage scenarios involving both the disciplines of the Internet of Things (IoT) and edge computing. This is especially true in manufacturing and industrial engineering.

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Private cloud use cases: 6 ways private cloud brings value to enterprise business

IBM Journey to AI blog

What is a private cloud? Moreover, while an organization may choose to run and manage a private cloud themselves, they frequently outsource partial or full management to a third-party provider. billion by 2033, up from USD 92.64 billion in 2023. billion by 2033, up from USD 92.64 billion in 2023.

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Public cloud vs. private cloud vs. hybrid cloud: What’s the difference?

IBM Journey to AI blog

That’s why it is essential to compare the different functionalities of private cloud versus public cloud versus hybrid cloud. What is cloud computing? What do private cloud, public cloud and hybrid cloud have in common? on-premises, private cloud, public cloud, edge) with public cloud services from more than one provider.

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ML Model Packaging [The Ultimate Guide]

The MLOps Blog

Or have you struggled to manage multiple versions of a model and keep track of all the dependencies and configurations required for deployment? Getting it right can mean the difference between a successful deployment and a project that may never see the light of day. What is model packaging in machine learning?

ML 69
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Definite Guide to Building a Machine Learning Platform

The MLOps Blog

From gathering and processing data to building models through experiments, deploying the best ones, and managing them at scale for continuous value in production—it’s a lot. But here’s the catch: understanding what makes a platform successful and building it is no easy feat. What is a machine learning platform?