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Core technologies and tools for AI, big data, and cloud computing

O'Reilly Media - Ideas

Many companies are just beginning to address the interplay between their suite of AI, big data, and cloud technologies. I’ll also highlight some interesting uses cases and applications of data, analytics, and machine learning. Data Platforms. Data Integration and Data Pipelines. Model lifecycle management.

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Which Government, Non-Profit and NGO Have Big Data/CDH Lessons Learned To Share?

CTOvision

Successfully deploying Hadoop as a core component or enterprise data hub within a symbiotic and interconnected big data ecosystem; integrating with existing relational data warehouse(s), data mart(s), and analytic systems, and supporting a wide range of user groups with different needs, skill sets, and workloads.

Big Data 105
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Data Analytics: Strategies to Demonstrate Value and Achieve Transformation

CIO

While “consumption” matters are just as critical, getting data supply right is essential to ensuring that data — and the insights it drives — are available and trustworthy. A community of teams Organizations can support data analytics program effectiveness by ensuring that all impacted stakeholders (e.g.,

Analytics 264
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What is data governance? Best practices for managing data assets

CIO

It must be clear to all participants and auditors how and when data-related decisions and controls were introduced into the processes. Data-related decisions, processes, and controls subject to data governance must be auditable. The program must introduce and support standardization of enterprise data.

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Building Trust in Public Sector AI Starts with Trusting Your Data

Cloudera

It is vital to establish stringent data governance practices to maintain data integrity, privacy, and compliance with regulatory requirements. Open-source solutions like Cloudera Data Flow and Open Data Lakehouse provide the necessary infrastructure and tools for governments to build and deploy trustworthy AI solutions at scale.

Data 111
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Intelligenza artificiale e gen AI: i quattro elementi per passare al “next level”

CIO

Altrettanto importante (e forse più trascurata) è la questione dei big data che servono per addestrare i modelli e il costo connesso. Tuttavia, in generale, se l’IA ha lavorato sui big data è difficile che il risultato non sia affidabile”. Che cosa posso fare con l’IA?

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From Data Swamp to Data Lake: Data Catalog

Perficient

The Data Catalog serves as an inventory of available data and provides information to evaluate the usefulness and quality of data to answer business questions and make better business decisions.

Data 110