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New Practices in Data Governance and Data Fabric for Telecommunications

Cloudera

As compliance rules change over time, new requirements may influence the choice of infrastructure: for example, Personally Identifiable Information (PII) or federal government data may be required to remain in the country. The post New Practices in Data Governance and Data Fabric for Telecommunications appeared first on Cloudera Blog.

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How is Hadoop Transforming the Telecommunication industry?

ProjectPro

The amount of big data telecommunication industry generates has high velocity and volume. In a hypercompetitive industry, to be profitable and successful telecommunication companies have to differentiate their offerings and target customers effectively. How big the telecommunication industry really is?

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Public or On-Prem? Telco giants are optimizing the network with the Hybrid Cloud

Cloudera

The telecommunications industry continues to develop hybrid data architectures to support data workload virtualization and cloud migration. Telco organizations are planning to move towards hybrid multi-cloud to manage data better and support their workforces in the near future. But not just the public cloud.

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Driving Standards & Collaboration in Telco with Data & AI

Cloudera

I’m thrilled to report that Cloudera today announced its membership of the TM Forum , the leading industry standards and collaboration group for the telecommunications industry. We’ve seen it evolve over the last ten years or so from a kind of skunkworks project to a core element of the CSP Enterprise Architecture.

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Modern Data Architecture for Telecommunications

Cloudera

In the wake of the disruption caused by the world’s turbulence over the past few years , the telecommunications industry has come out reasonably unscathed. Why telco should consider modern data architecture. What is the rationale for driving a modern data architecture? The challenges.

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Solutions Architect Job Roles in 2024 [Career Options]

Knowledge Hut

Data Solutions Architect Role Overview: Design and implement data management, storage, and analytics solutions to meet business requirements and enable data-driven decision-making. Role Level: Mid to senior-level position requiring expertise in data architecture, database technologies, and analytics platforms.

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The Top 3 Data Mesh Challenges — and How to Solve Them

Ascend.io

The core tenet of the data mesh is to distribute responsibility and governance of your data across different business “domains”. This is the opposite of having a single, monolithic data architecture managed by a centralized data team.