Remove Data Analytics Remove Data Governance Remove Data Processing Remove IoT
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Artificial intelligence and machine learning adoption in European enterprise

O'Reilly on Data

In practice this means developing a coherent strategy for integrating artificial intelligence (AI), big data, and cloud components, and specifically investing in foundational technologies needed to sustain the sensible use of data, analytics, and machine learning. Data Platforms. Data Integration and Data Pipelines.

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Announcing the 2021 Data Impact Awards

Cloudera

2020 saw us hosting our first ever fully digital Data Impact Awards ceremony, and it certainly was one of the highlights of our year. We saw a record number of entries and incredible examples of how customers were using Cloudera’s platform and services to unlock the power of data. DATA FOR ENTERPRISE AI.

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The DataOps Vendor Landscape, 2021

DataKitchen

We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . DataKitchen — a DataOps Platform that supports the deployment of all data analytics code and configuration.

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Big Data Analytics Is The 21st Century’s Biggest Disruptor In Healthcare

Smart Data Collective

By definition, big data in health IT applies to electronic datasets so vast and complex that they are nearly impossible to capture, manage, and process with common data management methods or traditional software/hardware. Big data analytics: solutions to the industry challenges. Big data storage.

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Accelerate Agency Missions with Data in Motion

Cloudera

Every level of government is awash in data (both structured and unstructured) that is perpetually in motion. It is constantly generated – and always growing in volume – by an ever-growing range of sources, from IoT sensors and other connected devices at the edge to web and social media to video and more.

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