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Data Storage Formats for Big Data Analytics: Performance and Cost Implications of Parquet, Avro, and ORC

DZone

Efficient data processing is crucial for businesses and organizations that rely on big data analytics to make informed decisions. One key factor that significantly affects the performance of data processing is the storage format of the data.

Big Data 278
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AI techniques enhance and accelerate exploratory data analytics

Dynatrace

In a digital-first world, site reliability engineers and IT data analysts face numerous challenges with data quality and reliability in their quest for cloud control. Increasingly, organizations seek to address these problems using AI techniques as part of their exploratory data analytics practices.

Analytics 222
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Advanced analytics: Leverage edge IoT data with OpenTelemetry and Dynatrace

Dynatrace

In today’s data-driven world, businesses across various industry verticals increasingly leverage the Internet of Things (IoT) to drive efficiency and innovation. Both methods allow you to ingest and process raw data and metrics. The ADS-B protocol differs significantly from web technologies.

IoT 223
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What is security analytics?

Dynatrace

As a result, organizations are implementing security analytics to manage risk and improve DevSecOps efficiency. Fortunately, CISOs can use security analytics to improve visibility of complex environments and enable proactive protection. What is security analytics? Why is security analytics important? Here’s how.

Analytics 243
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Real-time business analytics with Dynatrace: Unleashing the treasure trove of insights from your observability data

Dynatrace

Driven by that value, Dynatrace brings real-time observability, security, and business data into context and makes sense of it so our customers can get answers, automate, predict, and prevent. Executives are sitting on a goldmine of data, and they don’t know it. Common business analytics incur too much latency.

Analytics 219
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Unlock the power of contextual log analytics

Dynatrace

Existing siloed tools lead to inefficient workflows, fragmented data, and increased troubleshooting times. Rather than relying on disparate tools for each environment and team, Dynatrace integrates all data into one cohesive platform. As a result, dedicated data pipeline tools are unnecessary for preprocessing data before ingestion.

Analytics 247
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Real-Time Analytics

DZone

This is an article from DZone's 2023 Data Pipelines Trend Report. For more: Read the Report We live in an era of rapid data generation from countless sources, including sensors, databases, cloud, devices, and more. Stream processing is used to query a continuous stream of data and immediately process events in that stream.

Analytics 298