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The capabilities government leaders need as they manage the cloud’s data explosion

Dynatrace

A new Dynatrace report highlights the challenges for government and public-sector organizations as they increasingly rely on cloud-native architectures—and a corresponding data explosion. Distributed architectures create another challenge for governments and public-sector organizations.

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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 187
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Measuring the importance of data quality to causal AI success

Dynatrace

Traditional analytics and AI systems rely on statistical models to correlate events with possible causes. It starts with implementing data governance practices, which set standards and policies for data use and management in areas such as quality, security, compliance, storage, stewardship, and integration.

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DevSecOps: Recent experiences in field of Federal & Government

Dynatrace

In this blog we’re going to cover some of the recent, sometimes daily experiences I’ve encountered within Government and Federal agencies to demonstrate the role the Dynatrace platform plays to address these barriers and how agencies can leverage Dynatrace as an invaluable resource that contributes to DevSecOps success.

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What is Greenplum Database? Intro to the Big Data Database

Scalegrid

In this blog post, we explain what Greenplum is, and break down the Greenplum architecture, advantages, major use cases, and how to get started. Greenplum Database is an open-source , hardware-agnostic MPP database for analytics, based on PostgreSQL and developed by Pivotal who was later acquired by VMware. The Greenplum Architecture.

Big Data 321
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What is a data lakehouse? Combining data lakes and warehouses for the best of both worlds

Dynatrace

While data lakes and data warehousing architectures are commonly used modes for storing and analyzing data, a data lakehouse is an efficient third way to store and analyze data that unifies the two architectures while preserving the benefits of both. This is simply not possible with conventional architectures. Disadvantages.

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Causal AI use cases for modern observability that can transform any business

Dynatrace

Software developers can use causal analysis to identify the root causes of bugs or application performance issues and to predict potential system failures or performance degradations. Government. Government agencies can learn from cause-and-effect relationships to make more evidence-based policy decisions.