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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
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Dynatrace OpenPipeline: Stream processing data ingestion converges observability, security, and business data at massive scale for analytics and automation in context

Dynatrace

Organizations choose data-driven approaches to maximize the value of their data, achieve better business outcomes, and realize cost savings by improving their products, services, and processes. However, there are many obstacles and limitations along the way to becoming a data-driven organization.

Analytics 201
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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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What is a Distributed Storage System

Scalegrid

A distributed storage system is foundational in today’s data-driven landscape, ensuring data spread over multiple servers is reliable, accessible, and manageable. Understanding distributed storage is imperative as data volumes and the need for robust storage solutions rise.

Storage 130
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Privacy spotlight: Control compliance in Dynatrace with multiple layers of sensitive data masking

Dynatrace

Observing complex environments involves handling regulatory, compliance, and data governance requirements. This continuously evolving landscape requires careful management and clarity regarding how sensitive data is used. This is particularly important when dealing with large volumes of data.

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Storage handling improvements increase retention of transaction data for Dynatrace Managed

Dynatrace

Using existing storage resources optimally is key to being able to capture the right data over time. In this blog post, we announce: Compression of transaction data that’s older than three days. Improvements to Adaptive Data Retention. Transaction-data compression for Dynatrace Managed environments.

Storage 207
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How a data lakehouse brings data insights to life

Dynatrace

For IT infrastructure managers and site reliability engineers, or SREs , logs provide a treasure trove of data. But on their own, logs present just another data silo as IT professionals attempt to troubleshoot and remediate problems. Data volume explosion in multicloud environments poses log issues.

Analytics 231