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Real-time Data, Machine Learning, and Results: The Evidence Mounts

CIO Business Intelligence

It’s yet another key piece of evidence showing that there is a tangible return on a data architecture that is cloud-based and modernized – or, as this new research puts it, “coherent.”. Data architecture coherence. That represents a 24-point bump over those organizations where real time data wasn’t a priority.

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Innocens BV leverages IBM Technology to Develop an AI Solution to help detect potential sepsis events in high-risk newborns

IBM Big Data Hub

The specific approach we took required the use of both AI and edge computing to create a predictive model that could process years of anonymized data to help doctors make informed decisions. We wanted to be able to help them observe and monitor the thousands of data points available to make informed decisions.

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Real estate CIOs drive deals with data

CIO Business Intelligence

As for Keller Williams, Chief Technology and Digital Officer Chris Cox sees the cloud as an engine for innovation. “We We made a commitment to be truly cloud native and build an architecture that wasn’t burdened by any legacy infrastructure,” says Cox. minutes from the moment the property is listed.

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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

To pursue a data science career, you need a deep understanding and expansive knowledge of machine learning and AI. Having the right data strategy and data architecture is especially important for an organization that plans to use automation and AI for its data analytics.

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Getting Your First Job in Data Science

Data Science 101

Data scientists are the bridge between programming and algorithmic thinking. A data scientist can run a project from end-to-end. They can clean large amounts of data, explore data sets to find trends, build predictive models, and create a story around their findings. Data Analysts.

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Perform data parity at scale for data modernization programs using AWS Glue Data Quality

AWS Big Data

Arunabha Datta is a Senior Data Architect at AWS Professional Services. He collaborates with customers and partners to create and execute modern data architecture using AWS Analytics services. Charishma Ravoori is an Associate Data & ML Engineer at AWS Professional Services.

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Four Ways Telcos Can Realize Data-Driven Transformation

Cloudera

While navigating so many simultaneous data-dependent transformations, they must balance the need to level up their data management practices—accelerating the rate at which they ingest, manage, prepare, and analyze data—with that of governing this data.