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Navigate end-to-end data compliance through effective log management

Dynatrace

With an increasing number of regulations and standards governing how businesses handle data, an end-to-end compliance strategy is crucial. By ensuring that all processes—from data collection to storage and usage—comply with regulatory requirements, organizations can better manage potential threats.

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New continuous compliance requirements drive the need to converge observability and security

Dynatrace

The Hong Kong Monetary Authority (HKMA)’s Operational Resilience Framework provides guidance for Authorized Institutions (AIs) to ensure the continuity of critical operations during disruptions: governance, risk management, business continuity planning, and oversight of third-party dependencies. Were challenging these preconceptions.

Analytics 289
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Privacy spotlight: Control compliance in Dynatrace with multiple layers of sensitive data masking

Dynatrace

Observing complex environments involves handling regulatory, compliance, and data governance requirements. The whole experience is designed to fit into your individual data governance and compliance framework. Masking at storage: Data is persistently masked upon ingestion into Dynatrace.

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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. A lack of visibility into cloud environments .

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What is Greenplum Database? Intro to the Big Data Database

Scalegrid

High performance, query optimization, open source and polymorphic data storage are the major Greenplum advantages. Polymorphic Data Storage. Greenplum’s polymorphic data storage allows you to control the configuration for your table and partition storage with the freedom to execute and compress files within it at any time.

Big Data 321
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Introducing Impressions at Netflix

The Netflix TechBlog

The enriched data is seamlessly accessible for both real-time applications via Kafka and historical analysis through storage in an Apache Iceberg table. This refined output is then structured using an Avro schema, establishing a definitive source of truth for Netflixs impression data.

Tuning 166
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Dynatrace AI-powered platform operates on AWS Tokyo

Dynatrace

Domain-specific guidelines recommend local data storage in Japan. Government cloud services must use Japanese data centers. However, discussions with Dynatrace customers and prospects indicate that Japanese customers often require their data to be stored in Japan, especially in highly regulated industries like finance and healthcare.

AWS 278