Remove Data Governance Remove Data Integration Remove Data Science
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How companies are building sustainable AI and ML initiatives

O'Reilly on Data

In other words, could we see a roadmap for transitioning from legacy cases (perhaps some business intelligence) toward data science practices, and from there into the tooling required for more substantial AI adoption? Data scientists and data engineers are in demand.

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How EUROGATE established a data mesh architecture using Amazon DataZone

AWS Big Data

For container terminal operators, data-driven decision-making and efficient data sharing are vital to optimizing operations and boosting supply chain efficiency. Two use cases illustrate how this can be applied for business intelligence (BI) and data science applications, using AWS services such as Amazon Redshift and Amazon SageMaker.

IoT 100
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What is data governance? Best practices for managing data assets

CIO Business Intelligence

Data governance definition Data governance is a system for defining who within an organization has authority and control over data assets and how those data assets may be used. It encompasses the people, processes, and technologies required to manage and protect data assets.

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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. . Piperr.io — Pre-built data pipelines across enterprise stakeholders, from IT to analytics, tech, data science and LoBs.

Testing 300
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Artificial intelligence and machine learning adoption in European enterprise

O'Reilly on Data

Our survey showed that companies are beginning to build some of the foundational pieces needed to sustain ML and AI within their organizations: Solutions, including those for data governance, data lineage management, data integration and ETL, need to integrate with existing big data technologies used within companies.

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Becoming a machine learning company means investing in foundational technologies

O'Reilly on Data

Not surprisingly, data integration and ETL were among the top responses, with 60% currently building or evaluating solutions in this area. In an age of data-hungry algorithms, everything really begins with collecting and aggregating data. Key features of many data science platforms. Source: O'Reilly.

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Denodo and the Gartner Peer Insights™ Voice of the Customer for Data Integration Tools, 2024

Data Virtualization

Reading Time: 3 minutes Data integration is an important part of Denodo’s broader logical data management capabilities, which include data governance, a universal semantic layer, and a full-featured, business-friendly data catalog that not only lists all available data but also enables immediate access directly.