Remove Big Data Remove Latency Remove Speed
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What is a data lakehouse? Combining data lakes and warehouses for the best of both worlds

Dynatrace

Let’s explore what constitutes a data lakehouse, how it works, its pros and cons, and how it differs from data lakes and data warehouses. What is a data lakehouse? Data warehouses offer a single storage repository for structured data and provide a source of truth for organizations. Data management.

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What is ITOps? Why IT operations is more crucial than ever in a multicloud world

Dynatrace

This includes response time, accuracy, speed, throughput, uptime, CPU utilization, and latency. AIOps (artificial intelligence for IT operations) combines big data, AI algorithms, and machine learning for actionable, real-time insights that help ITOps continuously improve operations. Performance. ITOps vs. AIOps.

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Allez, rendez-vous à Paris – An AWS Region is coming to France!

All Things Distributed

Based in the Paris area, the region will provide even lower latency and will allow users who want to store their content in datacenters in France to easily do so. Today, I am very excited to announce our plans to open a new AWS Region in France! The new region in France will be ready for customers to use in 2017.

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How observability analytics helps teams uncover answers

Dynatrace

While measuring app response time under different circumstances provides a latency value, for example, it doesn’t tell you why the app is slow, fast, or somewhere in between. Data lakehouse Data lakes are a cost-efficient way to store information, while data warehouses provide contextual, high-speed querying capabilities.

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Experiences with approximating queries in Microsoft’s production big-data clusters

The Morning Paper

Experiences with approximating queries in Microsoft’s production big-data clusters Kandula et al., Microsoft’s big data clusters have 10s of thousands of machines, and are used by thousands of users to run some pretty complex queries. Five queries improve substantially on both latency and total compute hours.

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Incremental Processing using Netflix Maestro and Apache Iceberg

The Netflix TechBlog

Whether in analyzing A/B tests, optimizing studio production, training algorithms, investing in content acquisition, detecting security breaches, or optimizing payments, well structured and accurate data is foundational. Backfill: Backfilling datasets is a common operation in big data processing. append, overwrite, etc.).

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Expanding the Cloud - Introducing the AWS Asia Pacific (Tokyo.

All Things Distributed

Japanese companies and consumers have become used to low latency and high-speed networking available between their businesses, residences, and mobile devices. The advanced Asia Pacific network infrastructure also makes the AWS Tokyo Region a viable low-latency option for customers from South Korea.

AWS 92