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Medallion Architecture: Efficient Batch and Stream Processing Data Pipelines With Azure Databricks and Delta Lake

DZone

In today's data-driven world, organizations need efficient and scalable data pipelines to process and analyze large volumes of data. Medallion Architecture provides a framework for organizing data processing workflows into different zones, enabling optimized batch and stream processing.

Azure 246
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Exploring Parallel Processing: SIMD vs. MIMD Architectures

DZone

In the landscape of computer architecture, two prominent paradigms shape the realm of parallel processing: SIMD (Single Instruction, Multiple Data) and MIMD (Multiple Instruction, Multiple Data) architectures. This approach enables efficient processing of large datasets by applying the same operation to multiple elements concurrently.

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Improving customer experience with business process monitoring

Dynatrace

A business process is a collection of related, usually structured tasks or steps, performed in sequence, that achieve a defined business goal. Tasks may be manual or automatic, and many business processes will include a combination of both. Make better decisions by providing managers with real-time data about the business.

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Business Flow: Why IT operations teams should monitor business processes

Dynatrace

The business process observability challenge Increasingly dynamic business conditions demand business agility; reacting to a supply chain disruption and optimizing order fulfillment are simple but illustrative examples. Most business processes are not monitored. First and foremost, it’s a data problem.

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Energy Efficient Distributed Systems

DZone

Energy efficiency has become a paramount concern in the design and operation of distributed systems due to the increasing demand for sustainable and environmentally friendly computing solutions.

Energy 169
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Batch Processing: 4 Tactics to Make It Cost-Efficient and Reliable

DZone

Many modern applications have a batch processing aspect to them and regularly run high-volume, repetitive data jobs. Here are the four tactics for cost-efficient and resilient batch processing: Here are the four tactics for cost-efficient and resilient batch processing:

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Cutting Big Data Costs: Effective Data Processing With Apache Spark

DZone

In today's data-driven world, efficient data processing plays a pivotal role in the success of any project. Apache Spark , a robust open-source data processing framework, has emerged as a game-changer in this domain.

Big Data 269