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Batch Processing for Data Integration

DZone

In the labyrinth of data-driven architectures, the challenge of data integration—fusing data from disparate sources into a coherent, usable form — stands as one of the cornerstones. As businesses amass data at an unprecedented pace, the question of how to integrate this data effectively comes to the fore.

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Data Integration in Real-Time Systems

DZone

In the rapidly evolving digital landscape, the role of data has shifted from being merely a byproduct of business to becoming its lifeblood. With businesses constantly in the race to stay ahead, the process of integrating this data becomes crucial.

Systems 281
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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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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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Supporting Diverse ML Systems at Netflix

The Netflix TechBlog

Berg , Romain Cledat , Kayla Seeley , Shashank Srikanth , Chaoying Wang , Darin Yu Netflix uses data science and machine learning across all facets of the company, powering a wide range of business applications from our internal infrastructure and content demand modeling to media understanding.

Systems 226
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Why applying chaos engineering to data-intensive applications matters

Dynatrace

The jobs executing such workloads are usually required to operate indefinitely on unbounded streams of continuous data and exhibit heterogeneous modes of failure as they run over long periods. Performance is usually a primary concern when using stream processing frameworks.

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Stream Processing vs. Batch Processing: What to Know

DZone

Big data is at the center of all business decisions these days. It refers to large volumes of data generated through different sources, and this data then provides the foundation for business decisions. There are different ways through which we can process data. What Is Batch Processing?