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ETL Pipeline using Shell Scripting | Data Pipeline

Analytics Vidhya

Introduction ETL pipelines can be built from bash scripts. You will learn about how shell scripting can implement an ETL pipeline, and how ETL scripts or tasks can be scheduled using shell scripting. The post ETL Pipeline using Shell Scripting | Data Pipeline appeared first on Analytics Vidhya.

ETL 306
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Developing an End-to-End Automated Data Pipeline

Analytics Vidhya

Introduction Data acclimates to countless shapes and sizes to complete its journey from a source to a destination. Be it a streaming job or a batch job, ETL and ELT are irreplaceable. Before designing an ETL job, choosing optimal, performant, and cost-efficient tools […].

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CI/CD for Data Pipelines: A Game-Changer with AnalyticsCreator

Data Science Blog

Continuous Integration and Continuous Delivery (CI/CD) for Data Pipelines: It is a Game-Changer with AnalyticsCreator! The need for efficient and reliable data pipelines is paramount in data science and data engineering. They transform data into a consistent format for users to consume.

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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.

ETL 135
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Serverless High Volume ETL data processing on Code Engine

IBM Data Science in Practice

By Santhosh Kumar Neerumalla , Niels Korschinsky & Christian Hoeboer Introduction This blogpost describes how to manage and orchestrate high volume Extract-Transform-Load (ETL) loads using a serverless process based on Code Engine. The source data is unstructured JSON, while the target is a structured, relational database.

ETL 100
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What is Data Pipeline? A Detailed Explanation

Smart Data Collective

Data pipelines automatically fetch information from various disparate sources for further consolidation and transformation into high-performing data storage. There are a number of challenges in data storage , which data pipelines can help address. Choosing the right data pipeline solution.

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Understanding ETL Tools as a Data-Centric Organization

Smart Data Collective

The ETL process is defined as the movement of data from its source to destination storage (typically a Data Warehouse) for future use in reports and analyzes. The data is initially extracted from a vast array of sources before transforming and converting it to a specific format based on business requirements.

ETL 126