Remove Analytics Remove Big Data Remove Latency
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In-Stream Big Data Processing

Highly Scalable

The shortcomings and drawbacks of batch-oriented data processing were widely recognized by the Big Data community quite a long time ago. This system has been designed to supplement and succeed the existing Hadoop-based system that had too high latency of data processing and too high maintenance costs. References.

Big Data 154
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What is a data lakehouse? Combining data lakes and warehouses for the best of both worlds

Dynatrace

Generally, the storage technology categorizes data into landing, raw, and curated zones depending on its consumption readiness. The result is a framework that offers a single source of truth and enables companies to make the most of advanced analytics capabilities simultaneously. Support diverse analytics workloads.

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Probabilistic Data Structures for Web Analytics and Data Mining

Highly Scalable

Statistical analysis and mining of huge multi-terabyte data sets is a common task nowadays, especially in the areas like web analytics and Internet advertising. Analysis of such large data sets often requires powerful distributed data stores like Hadoop and heavy data processing with techniques like MapReduce.

Analytics 191
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Bulldozer: Batch Data Moving from Data Warehouse to Online Key-Value Stores

The Netflix TechBlog

Data scientists and engineers collect this data from our subscribers and videos, and implement data analytics models to discover customer behaviour with the goal of maximizing user joy. The data warehouse is not designed to serve point requests from microservices with low latency.

Latency 248
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No need to compromise visibility in public clouds with the new Azure services supported by Dynatrace

Dynatrace

Our customers have frequently requested support for this first new batch of services, which cover databases, big data, networks, and computing. See the health of your big data resources at a glance. Azure HDInsight supports a broad range of use cases including data warehousing, machine learning, and IoT analytics.

Azure 227
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Data Movement in Netflix Studio via Data Mesh

The Netflix TechBlog

Netflix is known for its loosely coupled microservice architecture and with a global studio footprint, surfacing and connecting the data from microservices into a studio data catalog in real time has become more important than ever. Data Mesh leverages Iceberg tables as data warehouse sinks for downstream analytics use cases.

Big Data 255
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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. What does IT operations do?