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Building AI-Powered Data Pipelines: Streamlining Elasticsearch to BigQuery Integration with Python

EasyChair Preprint 15162

7 pagesDate: September 29, 2024

Abstract

In the era of big data, organizations rely on efficient data pipelines to transfer, process, and analyze vast datasets. This article explores the creation of AI-powered data pipelines, specifically focusing on the integration between Elasticsearch and BigQuery. It highlights the key techniques to streamline the data flow between these platforms, enhancing the potential for AI-driven insights. The goal is to demonstrate how businesses can optimize data management and analytics by building robust, scalable, and intelligent data pipelines.

Keyphrases: AI-powered pipelines, Big Data, BigQuery, Data Analytics, ETL, Elasticsearch, data integration, machine learning

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@booklet{EasyChair:15162,
  author    = {Toluwani Bolu},
  title     = {Building AI-Powered Data Pipelines: Streamlining Elasticsearch to BigQuery Integration with Python},
  howpublished = {EasyChair Preprint 15162},
  year      = {EasyChair, 2024}}
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