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The top four log analytics and log management best practices

Dynatrace

By following key log analytics and log management best practices, teams can get more business value from their data. Challenges driving the need for log analytics and log management best practices As organizations undergo digital transformation and adopt more cloud computing techniques, data volume is proliferating.

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How unified data and analytics offers a new approach to software intelligence

Dynatrace

IT pros want a data and analytics solution that doesn’t require tradeoffs between speed, scale, and cost. With a data and analytics approach that focuses on performance without sacrificing cost, IT pros can gain access to answers that indicate precisely which service just went down and the root cause.

Analytics 196
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Site-Speed Topography

CSS Wizardry

When first working on a new site-speed engagement, you need to work out quickly where the slowdowns, blindspots, and inefficiencies lie. Google Analytics can show us individual slow pages, but doesn’t necessarily help us build a bigger picture of the site as a whole. See entry 6. That work is what comes next.

Speed 292
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Optimize mobile app performance, adoption, and conversions with Session Replay and business analytics

Dynatrace

New technologies like Xamarin or React Native are accelerating the speed at which organizations release new features and unlock market reach. How do I connect the dots between mobile analytics and performance monitoring? Connect the dots between mobile analytics and performance monitoring with mobile business analytics.

Analytics 211
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Google Analytics and Dynatrace – Why you need both

Dynatrace

In this post, I wanted to share how I use Google Analytics together with Dynatrace to give me a more complete picture of my customers, and their experience across our digital channels. Google Analytics. Almost all marketers will be familiar with Google Analytics. Digital and Business Analytics. So we turned it off.

Google 153
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What is a data lakehouse? Combining data lakes and warehouses for the best of both worlds

Dynatrace

A data lakehouse features the flexibility and cost-efficiency of a data lake with the contextual and high-speed querying capabilities of a data warehouse. The result is a framework that offers a single source of truth and enables companies to make the most of advanced analytics capabilities simultaneously. What is a data lakehouse?

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The history of Grail: Why you need a data lakehouse

Dynatrace

Grail needs to support security data as well as business analytics data and use cases. With that in mind, Grail needs to achieve three main goals with minimal impact to cost: Cope with and manage an enormous amount of data —both on ingest and analytics. High-performance analytics—no indexing required.