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AI techniques enhance and accelerate exploratory data analytics

Dynatrace

Increasingly, organizations seek to address these problems using AI techniques as part of their exploratory data analytics practices. Another hurdle is mistaking easy patterns as effective analysis, according to an article in the Harvard Data Science Review.

Analytics 215
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Dynatrace unveils Security Analytics to elevate threat detection, forensics, and incident response

Dynatrace

A traditional log-based SIEM approach to security analytics may have served organizations well in simpler on-premises environments. Security Analytics and automation deal with unknown-unknowns With Security Analytics, analysts can explore the unknown-unknowns, facilitating queries manually in an ad hoc way, or continuously using automation.

Analytics 223
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Conducting log analysis with an observability platform and full data context

Dynatrace

Modern organizations ingest petabytes of data daily, but legacy approaches to log analysis and management cannot accommodate this volume of data. Traditional log analysis evaluates logs and enables organizations to mitigate myriad risks and meet compliance regulations. Grail enables 100% precision insights into all stored data.

Analytics 192
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Intelligent observability for Oracle and SQL databases

Dynatrace

While applications are built using a variety of technologies and frameworks, there is one thing they usually have in common: the data they work with must be stored in databases. Now, Dynatrace has gone a step further and expanded its coverage and intelligent observability into the next layer: database infrastructure.

Database 243
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Extend business observability: Extract business events from online databases (Part 1)

Dynatrace

Additionally, Dynatrace business events enable organizations to explore and analyze large, long-term data sets without pre-indexing, which allows for flexible and comprehensive data analysis. There are also many cases where business data—transactional, inventory, or financial—is at rest or in use , stored in a database.

Database 231
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What is log analytics? How a modern observability approach provides critical business insight

Dynatrace

What is log analytics? Log analytics is the process of viewing, interpreting, and querying log data so developers and IT teams can quickly detect and resolve application and system issues. This is also known as root-cause analysis. What are the use cases for log analytics? Peak performance analysis. Dynatrace news.

Analytics 220
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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 193