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What is Greenplum Database? Intro to the Big Data Database

Scalegrid

When handling large amounts of complex data, or big data, chances are that your main machine might start getting crushed by all of the data it has to process in order to produce your analytics results. Greenplum features a cost-based query optimizer for large-scale, big data workloads. Query Optimization.

Big Data 321
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Sustainability: Thoughts from a software engineer

Dynatrace

Until recently, improvements in data center power efficiency compensated almost entirely for the increasing demand for computing resources. The rise of big data, cryptocurrencies, and AI means the IT sector contributes significantly to global greenhouse gas emissions. However, this trend is now reversing.

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In-Stream Big Data Processing

Highly Scalable

The shortcomings and drawbacks of batch-oriented data processing were widely recognized by the Big Data community quite a long time ago. The design of the in-stream processing engine itself was driven by the following requirements: SQL-like functionality. Strict fault-tolerance is a principal requirement for the engine.

Big Data 154
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A Recap of the Data Engineering Open Forum at Netflix

The Netflix TechBlog

A summary of sessions at the first Data Engineering Open Forum at Netflix on April 18th, 2024 The Data Engineering Open Forum at Netflix on April 18th, 2024. At Netflix, we aspire to entertain the world, and our data engineering teams play a crucial role in this mission by enabling data-driven decision-making at scale.

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Data Engineers of Netflix?—?Interview with Pallavi Phadnis

The Netflix TechBlog

Data Engineers of Netflix?—?Interview Interview with Pallavi Phadnis This post is part of our “ Data Engineers of Netflix ” series, where our very own data engineers talk about their journeys to Data Engineering @ Netflix. Pallavi Phadnis is a Senior Software Engineer at Netflix.

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Less is More: Engineering Data Warehouse Efficiency with Minimalist Design

Uber Engineering

Maintaining Uber’s large-scale data warehouse comes with an operational cost in terms of ETL functions and storage. In our experience, optimizing for operational efficiency requires answering one key question: for which tables does the maintenance cost supersede utility?

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What is IT operations analytics? Extract more data insights from more sources

Dynatrace

In addition to improved IT operational efficiency at a lower cost, ITOA also enhances digital experience monitoring for increased customer engagement and satisfaction. Then, big data analytics technologies, such as Hadoop, NoSQL, Spark, or Grail, the Dynatrace data lakehouse technology, interpret this information.

Analytics 246