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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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Huawei unveils four strategic directions for the future of finance

CIO Business Intelligence

“We use the peer-to-peer computing of CPUs, GPUs, and NPUs to enable the multi-active data center to run efficiently, just like a computer,” Mr. Cao told the conference. The distributed architecture now outperforms the original core host platform, notably with lower latency. Huawei’s new Data Intelligence Solution 3.0

Finance 97
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Building resilient infrastructure: the key to cloud-native, real-time decision-making

CIO Business Intelligence

“We use the peer-to-peer computing of CPUs, GPUs, and NPUs to enable the multi-active data center to run efficiently, just like a computer,” Mr. Cao told the conference. The distributed architecture now outperforms the original core host platform, notably with lower latency. Huawei’s new Data Intelligence Solution 3.0

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Eight Top DataOps Trends for 2022

DataKitchen

DataOps adoption continues to expand as a perfect storm of social, economic, and technological factors drive enterprises to invest in process-driven innovation. As a result, enterprises will examine their end-to-end data operations and analytics creation workflows. Data Gets Meshier.

Testing 245
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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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The power of remote engine execution for ETL/ELT data pipelines

IBM Big Data Hub

Organizations require reliable data for robust AI models and accurate insights, yet the current technology landscape presents unparalleled data quality challenges. As a result, users boost pipeline performance while ensuring data security and controls. However, businesses scaling AI face entry barriers.