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Introduction to Azure Data Lake Storage Gen2

DZone

Built on Azure Blob Storage, Azure Data Lake Storage Gen2 is a suite of features for big data analytics. Azure Data Lake Storage Gen1 and Azure Blob Storage's capabilities are combined in Data Lake Storage Gen2.

Azure 243
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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. Understanding the context.

Analytics 198
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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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Adding business analytics data to your observability strategy delivers better business outcomes

Dynatrace

To stay competitive in an increasingly digital landscape, organizations seek easier access to business analytics data from IT to make better business decisions faster. As organizations add more tools, it creates a demand for common tooling, shared data, and democratized access. But getting the value out of the data is not easy.

Analytics 194
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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 240
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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 226
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Data lakehouse innovations advance the three pillars of observability for more collaborative analytics

Dynatrace

How do you get more value from petabytes of exponentially exploding, increasingly heterogeneous data? The short answer: The three pillars of observability—logs, metrics, and traces—converging on a data lakehouse. To solve this problem, Dynatrace launched Grail, its causational data lakehouse , in 2022.

Analytics 191