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The DataOps Vendor Landscape, 2021

DataKitchen

Testing and Data Observability. 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. . Genie — Distributed big data orchestration service by Netflix.

Testing 304
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The future of data: A 5-pillar approach to modern data management

CIO Business Intelligence

The proposed model illustrates the data management practice through five functional pillars: Data platform; data engineering; analytics and reporting; data science and AI; and data governance. This development will make it easier for smaller organizations to start incorporating AI/ML capabilities.

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7 types of tech debt that could cripple your business

CIO Business Intelligence

For this reason, organizations with significant data debt may find pursuing many gen AI opportunities more challenging and risky. What CIOs can do: Avoid and reduce data debt by incorporating data governance and analytics responsibilities in agile data teams , implementing data observability , and developing data quality metrics.

Risk 140
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HEMA accelerates their data governance journey with Amazon DataZone

AWS Big Data

Each service is hosted in a dedicated AWS account and is built and maintained by a product owner and a development team, as illustrated in the following figure. Implementing robust data governance is challenging. In a data mesh architecture, this complexity is amplified by the organizations decentralized nature.

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Expanding data analysis and visualization options: Amazon DataZone now integrates with Tableau, Power BI, and more

AWS Big Data

With this launch of JDBC connectivity, Amazon DataZone expands its support for data users, including analysts and scientists, allowing them to work in their preferred environments—whether it’s SQL Workbench, Domino, or Amazon-native solutions—while ensuring secure, governed access within Amazon DataZone. Choose Test connection.

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Cloudera AI Inference Service Enables Easy Integration and Deployment of GenAI Into Your Production Environments

Cloudera

It is a powerful deployment environment that enables you to integrate and deploy generative AI (GenAI) and predictive models into your production environments, incorporating Cloudera’s enterprise-grade security, privacy, and data governance. Why did we build it?

Metrics 73
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Data governance beyond SDX: Adding third party assets to Apache Atlas

Cloudera

In this blog, we’ll highlight the key CDP aspects that provide data governance and lineage and show how they can be extended to incorporate metadata for non-CDP systems from across the enterprise. h load-node-0 <-- host name of the server. -e e prod <-- environment (prod|pre-prod|test). -c