October 2024

The Magic of Data Pipelines & ETL

Can Data Pipelines Really Improve Data Quality, Processing, and Integration?

A data pipeline automates the flow of data between systems, enabling real-time and batch processing. It collects, transforms, and stores data from various sources like databases and APIs ensuring that large applications can efficiently handle growing volumes while staying responsive.

ETL (Extract, Transform, Load) is a specific type of data pipeline focused on preparing data for analysis. It extracts data from multiple sources, transforms it into a usable format, and loads it into a system for further processing. While ETL has always handled batch jobs, newer solutions support near real-time processing.

Together, pipelines and ETL ensure accurate, scalable data flow and analysis in large applications.

Here are some interesting articles related to this topic.

what-is-a-data-pipeline

What Is a Data Pipeline?

By Cole Striker

A data pipeline is a method by which raw data is ingested from various data sources, transformed, and ported to a data store, such as a data lake or data warehouse, for analysis.

This article provides a good overview of data pipelines including what they are, types of data pipelines, data pipeline architectures, and some use cases.

etl-best-practices

ETL Best Practices: Optimizing Your Data Integration Pipelines

By Revanth Periyasamy

In the era of big data and digital transformation, implementing ETL (Extract, Transform, Load) best practices has become more critical than ever. Organizations that neglect these practices can face severe consequences.

This article covers 15 essential ETL best practices to unlock the full potential of any data asset.

what-is-etl

What is ETL?

By IBM

ETL—extract, transform, load—is a data integration process that combines, cleans, and organizes data from multiple sources into a single, consistent data set for storage in a data warehouse, data lake or other target system.

This article provides a good overview of what ETL is, how ETL evolved, ETL vs ELT, how ETL works, benefits and challenges, tools, and other relevant topics.

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