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Building a Data Pipeline with PySpark and AWS

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction Apache Spark is a framework used in cluster computing environments. The post Building a Data Pipeline with PySpark and AWS appeared first on Analytics Vidhya.

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Build a Scalable Data Pipeline with Apache Kafka

Analytics Vidhya

Kafka is based on the idea of a distributed commit log, which stores and manages streams of information that can still work even […] The post Build a Scalable Data Pipeline with Apache Kafka appeared first on Analytics Vidhya. It was made on LinkedIn and shared with the public in 2011.

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Innovations in Analytics: Elevating Data Quality with GenAI

Towards AI

Image by author #2 Label: Enabling the use of previously unusable data Organizations often have large amounts of data that are unused due to low quality or lack of labeling. Natural Language Processing (NLP) is an example of where traditional methods can struggle with complex text data.

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Enhance your Amazon Redshift cloud data warehouse with easier, simpler, and faster machine learning using Amazon SageMaker Canvas

AWS Machine Learning Blog

A provisioned or serverless Amazon Redshift data warehouse. For this post we’ll use a provisioned Amazon Redshift cluster. Set up the Amazon Redshift cluster We’ve created a CloudFormation template to set up the Amazon Redshift cluster. A SageMaker domain. A QuickSight account (optional). Database name : Enter dev.

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Unlocking near real-time analytics with petabytes of transaction data using Amazon Aurora Zero-ETL integration with Amazon Redshift and dbt Cloud

Flipboard

While customers can perform some basic analysis within their operational or transactional databases, many still need to build custom data pipelines that use batch or streaming jobs to extract, transform, and load (ETL) data into their data warehouse for more comprehensive analysis. Choose Delete stack.

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Essential data engineering tools for 2023: Empowering for management and analysis

Data Science Dojo

Data engineering tools are software applications or frameworks specifically designed to facilitate the process of managing, processing, and transforming large volumes of data. It supports various data types and offers advanced features like data sharing and multi-cluster warehouses.

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Hammerspace Unveils the Fastest File System in the World for Training Enterprise AI Models at Scale

insideBIGDATA

This new category of storage architecture – Hyperscale NAS – is built on the tenants required for large language model (LLM) training and provides the speed to efficiently power GPU clusters of any size for GenAI, rendering and enterprise high-performance computing.