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What is Greenplum Database? Intro to the Big Data Database

Scalegrid

Greenplum Database is a massively parallel processing (MPP) SQL database that is built and based on PostgreSQL. It can scale towards a multi-petabyte level data workload without a single issue, and it allows access to a cluster of powerful servers that will work together within a single SQL interface where you can view all of the data.

Big Data 321
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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.

Retail 152
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Kubernetes in the wild report 2023

Dynatrace

The strongest Kubernetes growth areas are security, databases, and CI/CD technologies. Strongest Kubernetes growth areas are security, databases, and CI/CD technologies. Of the organizations in the Kubernetes survey, 71% run databases and caches in Kubernetes, representing a +48% year-over-year increase. Java, Go, and Node.js

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Conducting log analysis with an observability platform and full data context

Dynatrace

Using Grail to heal observability pains Grail logs not only store big data, but also map out dependencies to enable fast analytics and data reasoning. ” Weighing the value and cost of indexed databases vs. Grail With standard index databases, teams must choose relevant indexes before data ingestion.

Analytics 190
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RSA Guide 2023: Cloud application security remains core challenge for organizations

Dynatrace

2022 CISO Report: Retail sector – report Dive deep into the state of runtime vulnerability management in retail and how to protect your brand. Meanwhile, traditional databases have demonstrated limitations in increasingly complex and distributed cloud-native environments.

Cloud 189
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Driving Bandwidth Cost Down for AWS Customers. - All Things.

All Things Distributed

For Amazon retail, some of those dimensions are low pricing, large catalog, fast shipping, and convenience. For example, when our retail customers contributed to create larger economies of scale for Amazon.com, we used the savings to lower pricing such that our customers could also benefit. Driving down the cost of Big-Data analytics.

AWS 106
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A case for ELT

Abhishek Tiwari

Cheap storage and on-demand compute in the cloud coupled with the emergence of new big data frameworks and tools are forcing us to rethink the whole ETL and data warehousing architecture. Then we perform frequent batch ETL from application databases to a data warehouse. Classic ETL. Late transformation.