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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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Productionizing Distributed XGBoost to Train Deep Tree Models with Large Data Sets at Uber

Uber Engineering

Michelangelo , Uber’s machine learning (ML) platform, powers machine learning model training across various use cases at Uber, such as forecasting rider demand , fraud detection , food discovery and recommendation for Uber Eats , and improving the accuracy of … The post Productionizing Distributed XGBoost to Train Deep Tree Models with Large (..)

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Evolving from Rule-based Classifier: Machine Learning Powered Auto Remediation in Netflix Data…

The Netflix TechBlog

Operational automation–including but not limited to, auto diagnosis, auto remediation, auto configuration, auto tuning, auto scaling, auto debugging, and auto testing–is key to the success of modern data platforms. For unclassified errors, the job may be retried multiple times with the default retry policy.

Tuning 210
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What is IT automation?

Dynatrace

As organizations continue to adopt multicloud strategies, the complexity of these environments grows, increasing the need to automate cloud engineering operations to ensure organizations can enforce their policies and architecture principles. AI that is based on machine learning needs to be trained. Big data automation tools.

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Seer: leveraging big data to navigate the complexity of performance debugging in cloud microservices

The Morning Paper

Seer: leveraging big data to navigate the complexity of performance debugging in cloud microservices Gan et al., A DNN model is trained to recognise patterns in space and time that lead to QoS violations. This retraining uses transfer learning with weights from previous training rounds stored on disk as a starting point.

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Tackling the Pipeline Problem in the Architecture Research Community

ACM Sigarch

Computer architecture is an important and exciting field of computer science, which enables many other fields (eg. big-data processing, machine learning, quantum computing, and so on). For those of us who pursued computer architecture as a career, this is well understood. Why is that? Should we be alarmed as a community?

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Applying real-world AIOps use cases to your operations

Dynatrace

Artificial intelligence for IT operations, or AIOps, combines big data and machine learning to provide actionable insight for IT teams to shape and automate their operational strategy. It works without having to identify training data, then training and honing. Achieving autonomous operations.

DevOps 196