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What is IT operations analytics? Extract more data insights from more sources

Dynatrace

With 99% of organizations using multicloud environments , effectively monitoring cloud operations with AI-driven analytics and automation is critical. IT operations analytics (ITOA) with artificial intelligence (AI) capabilities supports faster cloud deployment of digital products and services and trusted business insights.

Analytics 197
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Any analysis, any time: Dynatrace Log Management and Analytics powered by Grail

Dynatrace

Log management and analytics is an essential part of any organization’s infrastructure, and it’s no secret the industry has suffered from a shortage of innovation for several years. Several pain points have made it difficult for organizations to manage their data efficiently and create actual value.

Analytics 243
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Data lakehouse innovations advance the three pillars of observability for more collaborative analytics

Dynatrace

The goal is to turn more data into insights so the whole organization can make data-driven decisions and automate processes. Grail data lakehouse delivers massively parallel processing for answers at scale Modern cloud-native computing is constantly upping the ante on data volume, variety, and velocity.

Analytics 195
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What is software automation? Optimize the software lifecycle with intelligent automation

Dynatrace

In what follows, we define software automation as well as software analytics and outline their importance. What is software analytics? This involves big data analytics and applying advanced AI and machine learning techniques, such as causal AI. We also discuss the role of AI for IT operations (AIOps) and more.

Software 196
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What is a Distributed Storage System

Scalegrid

This guide delves into how these systems work, the challenges they solve, and their essential role in businesses and technology. Understanding distributed storage is imperative as data volumes and the need for robust storage solutions rise. Variations within these storage systems are called distributed file systems.

Storage 130
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Data Engineers of Netflix?—?Interview with Pallavi Phadnis

The Netflix TechBlog

During earlier years of my career, I primarily worked as a backend software engineer, designing and building the backend systems that enable big data analytics. I developed many batch and real-time data pipelines using open source technologies for AOL Advertising and eBay.

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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. In addition, we survey the current and emerging technologies and provide a few implementation tips. Towards Unified Big Data Processing.

Big Data 154