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Pioneering customer-centric pricing models: Decoding ingest-centric vs. answer-centric pricing

Dynatrace

The rise of cloud-native microservice architectures further exacerbates this change. retail giant, initially tied to an ingest-centric pricing vendor, found itself manually curbing costs by limiting daily log ingestion to 3 TB and reducing retention periods. Beware, you might be surprised how cost-efficient most of the queries are!

Retail 242
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Data Mining Problems in Retail

Highly Scalable

Retail is one of the most important business domains for data science and data mining applications because of its prolific data and numerous optimization problems such as optimal prices, discounts, recommendations, and stock levels that can be solved using data analysis methods. However, many of these models are highly parametric (i.e.

Retail 152
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What is FinOps? How to keep cloud spend in check

Dynatrace

Spiraling cloud architecture and application costs have driven the need for new approaches to cloud spend. Today, many global industries implement FinOps, including telecommunications, retail, manufacturing, and energy conservation, as well as most Fortune 50 companies. This practice isn’t just about reducing costs.

Cloud 201
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Digital transformation strategies: Success stories from three digital transformation journeys

Dynatrace

Some of the benefits organizations seek from digital transformation journeys include the following: Increased DevOps automation and efficiency. Digital tools and technologies provide a more efficient way of doing things. Improved customer experience. Improved customer experience. Competitive advantage. federal agency.

Strategy 179
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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. It’s architecture was specially designed to manage large-scale data warehouses and business intelligence workloads by giving you the ability to spread your data out across a multitude of servers.

Big Data 321
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Conducting log analysis with an observability platform and full data context

Dynatrace

With more automated approaches to log monitoring and log analysis, however, organizations can gain visibility into their applications and infrastructure efficiently and with greater precision—even as cloud environments grow. Logs are automatically produced and time-stamped documentation of events relevant to cloud architectures.

Analytics 192
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Enhancing Azure data analytics and Azure observability with Dynatrace Grail

Dynatrace

Dynatrace Grail™ data lakehouse unifies the massive volume and variety of observability, security, and business data from cloud-native, hybrid, and multicloud environments while retaining the data’s context to deliver instant, cost-efficient, and precise analytics. Digital transformation 2.0

Azure 184