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Progress for big data in Kubernetes

O'Reilly Media - Data

These difficulties people are facing with containers and state have actually been very good for us at my day job because we build a system that provides a software-defined storage layer that can make a pretty good cloud-neutral distributed data platform. but until recently, this was mostly useful to attach to external storage systems.

Big Data 213
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CIOs must mind their own data confidence gap

CIO

Directors are often more accurate in their confidence assessments, because theyre swimming in the systems, not just reviewing summaries. The directors werent being pessimistic; they saw the gaps dashboards dont show, he says. You cant really say, No, I dont know what we can do with that.

Data 187
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The top 15 big data and data analytics certifications

CIO

Data and big data analytics are the lifeblood of any successful business. Getting the technology right can be challenging but building the right team with the right skills to undertake data initiatives can be even harder — a challenge reflected in the rising demand for big data and analytics skills and certifications.

Big Data 190
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The future of data: A 5-pillar approach to modern data management

CIO

Without this setup, there is a risk of building models that are too slow to respond to customers, exhibit training-serving skew over time and potentially harm customers due to lack of production model monitoring. If a model encounters an issue in production, it is better to return an error to customers rather than provide incorrect data.

Data 167
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Ground truth generation and review best practices for evaluating generative AI question-answering with FMEval

AWS Machine Learning - AI

Ground truth data in AI refers to data that is known to be factual, representing the expected use case outcome for the system being modeled. By providing an expected outcome to measure against, ground truth data unlocks the ability to deterministically evaluate system quality.

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A Brief Introduction to Big Data Applications and Hadoop

UruIT

Big data refers to the set of techniques used to store and/or process large amounts of data. . Usually, big data applications are one of two types: data at rest and data in motion. For this article, we’ll focus mainly on data at rest applications and on the Hadoop ecosystem specifically.

Big Data 120
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Handling real-time data operations in the enterprise

O'Reilly Media - Data

Getting DataOps right is crucial to your late-stage big data projects. Let's call these operational teams that focus on big data: DataOps teams. Companies need to understand there is a different level of operational requirements when you're exposing a data pipeline. A data pipeline needs love and attention.