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Leveraging Infrastructure as Code for Data Engineering Projects: A Comprehensive Guide

DZone

Data engineering projects often require the setup and management of complex infrastructures that support data processing, storage, and analysis. In this article, we will explore the benefits of leveraging IaC for data engineering projects and provide detailed implementation steps to get started.

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Building Netflix’s Distributed Tracing Infrastructure

The Netflix TechBlog

Now let’s look at how we designed the tracing infrastructure that powers Edgar. This insight led us to build Edgar: a distributed tracing infrastructure and user experience. Our distributed tracing infrastructure is grouped into three sections: tracer library instrumentation, stream processing, and storage.

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Overcoming Challenges and Best Practices for Data Migration From On-Premise to Cloud

DZone

Data migration is the process of moving data from one location to another, which is an essential aspect of cloud migration. Data migration involves transferring data from on-premise storage to the cloud. With the rapid adoption of cloud computing , businesses are moving their IT infrastructure to the cloud.

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Measuring the importance of data quality to causal AI success

Dynatrace

While this approach can be effective if the model is trained with a large amount of data, even in the best-case scenarios, it amounts to an informed guess, rather than a certainty. But to be successful, data quality is critical. Teams need to ensure the data is accurate and correctly represents real-world scenarios. Consistency.

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Stay in control of your data retention with Dynatrace Grail—from 10 days to 10 years

Dynatrace

Optimize cost and availability while staying compliant Observability data like logs and metrics provide automated answers, root cause detection, and security issues. Customer decisions about data retention are often determined by important security, privacy, and legal issues.

Analytics 216
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Boost DevOps maturity with observability and a data lakehouse

Dynatrace

ln a world driven by macroeconomic uncertainty, businesses increasingly turn to data-driven decision-making to stay agile. They’re unleashing the power of cloud-based analytics on large data sets to unlock the insights they and the business need to make smarter decisions. All of these factors challenge DevOps maturity.

DevOps 186
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What is predictive AI? How this data-driven technique gives foresight to IT teams

Dynatrace

They handle complex infrastructure, maintain service availability, and respond swiftly to incidents. Predictive AI uses machine learning, data analysis, statistical models, and AI methods to predict anomalies, identify patterns, and create forecasts. This data-driven approach fosters continuous refinement of processes and systems.