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Modern Data Architecture for Telecommunications

Cloudera

Data has continued to grow both in scale and in importance through this period, and today telecommunications companies are increasingly seeing data architecture as an independent organizational challenge, not merely an item on an IT checklist. Why telco should consider modern data architecture. The challenges.

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The Top Three Entangled Trends in Data Architectures: Data Mesh, Data Fabric, and Hybrid Architectures

Cloudera

Each of these trends claim to be complete models for their data architectures to solve the “everything everywhere all at once” problem. Data teams are confused as to whether they should get on the bandwagon of just one of these trends or pick a combination. First, we describe how data mesh and data fabric could be related.

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Four Ways Telcos Can Realize Data-Driven Transformation

Cloudera

While navigating so many simultaneous data-dependent transformations, they must balance the need to level up their data management practices—accelerating the rate at which they ingest, manage, prepare, and analyze data—with that of governing this data.

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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. 2- AI capability drives data monetization.

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Eight Top DataOps Trends for 2022

DataKitchen

Data Gets Meshier. 2022 will bring further momentum behind modular enterprise architectures like data mesh. The data mesh addresses the problems characteristic of large, complex, monolithic data architectures by dividing the system into discrete domains managed by smaller, cross-functional teams.

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The power of remote engine execution for ETL/ELT data pipelines

IBM Big Data Hub

These approaches minimize data movement, latencies, and egress fees by leveraging integration patterns alongside a remote runtime engine, enhancing pipeline performance and optimization, while simultaneously offering users flexibility in designing their pipelines for their use case.

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Empowering data mesh: The tools to deliver BI excellence

erwin

One such innovation gaining traction is the data mesh framework. The data mesh approach distributes data ownership and decentralizes data architecture, paving the way for enhanced agility and scalability. This empowers individual teams to own and manage their data.