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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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How Amazon is solving big-data challenges with data lakes

All Things Distributed

The Galaxy data lake was built in 2019 and now all the various teams are working on moving their data into it. A data lake is a centralized secure repository that allows you to store, govern, discover, and share all of your structured and unstructured data at any scale.

Big Data 209
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What is IT operations analytics? Extract more data insights from more sources

Dynatrace

Then, big data analytics technologies, such as Hadoop, NoSQL, Spark, or Grail, the Dynatrace data lakehouse technology, interpret this information. Here are the six steps of a typical ITOA process : Define the data infrastructure strategy. Establish data governance. Provide data literacy for stakeholders.

Analytics 187
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What is a data lakehouse? Combining data lakes and warehouses for the best of both worlds

Dynatrace

In a data lakehouse model, organizations first migrate data from sources into a data lake. Then, a subset of this data seamlessly filters through to become more curated and trusted data sets on which organizations set the required governance, use, and access rules. What are the features of a data lakehouse?

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How to Optimize Elasticsearch for Better Search Performance

DZone

In today's world, data is generated in high volumes and to make something out of it, extracted data is needed to be transformed, stored, maintained, governed and analyzed. These processes are only possible with a distributed architecture and parallel processing mechanisms that Big Data tools are based on.

Big Data 157
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Mastering Hybrid Cloud Strategy

Scalegrid

Workloads from web content, big data analytics, and artificial intelligence stand out as particularly well-suited for hybrid cloud infrastructure owing to their fluctuating computational needs and scalability demands.

Strategy 130
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Hybrid cloud infrastructure explained: Weighing the pros, cons, and complexities

Dynatrace

A hybrid cloud, however, combines public infrastructure and services with on-premises resources or a private data center to create a flexible, interconnected IT environment. Hybrid environments provide more options for storing and analyzing ever-growing volumes of big data and for deploying digital services.