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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. The higher the criticality and sensitivity to data downtime, the more engineering and automation are needed.

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What Is Data Governance? (And Why Your Organization Needs It)

erwin

Organizations with a solid understanding of data governance (DG) are better equipped to keep pace with the speed of modern business. In this post, the erwin Experts address: What Is Data Governance? Why Is Data Governance Important? What Is Good Data Governance? What Is Data Governance?

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The DataOps Vendor Landscape, 2021

DataKitchen

Process Analytics. 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. . Reflow — A system for incremental data processing in the cloud. Continuous Deployment.

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HEMA accelerates their data governance journey with Amazon DataZone

AWS Big Data

However, many companies today still struggle to effectively harness and use their data due to challenges such as data silos, lack of discoverability, poor data quality, and a lack of data literacy and analytical capabilities to quickly access and use data across the organization.

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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. Enhance agility by localizing changes within business domains and clear data contracts. Eliminate centralized bottlenecks and complex data pipelines.

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How Data Governance Protects Sensitive Data

erwin

How can companies protect their enterprise data assets, while also ensuring their availability to stewards and consumers while minimizing costs and meeting data privacy requirements? Data Security Starts with Data Governance. Lack of a solid data governance foundation increases the risk of data-security incidents.

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Artificial intelligence and machine learning adoption in European enterprise

O'Reilly on Data

In a recent survey , we explored how companies were adjusting to the growing importance of machine learning and analytics, while also preparing for the explosion in the number of data sources. Data Platforms. Data Integration and Data Pipelines. Data preparation, data governance, and data lineage.