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Sreenath Devineni

DZone Core CORE

Lead Data Engineer at CVS Health

US

Joined Jan 2024

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Reputation: 377
Pageviews: 63.5K
Articles: 5
Comments: 0
  • Articles
  • Trend Reports

Articles

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A Guide to Auto-Tagging and Lineage Tracking With OpenMetadata
Learn how to automate PII tagging, metadata management, and SQL lineage tracking with GPT-4, OpenMetadata, dbt, Trino, and Python for smarter data governance.
May 27, 2025
· 6,050 Views
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Real-Time Data Streaming on Cloud Platforms: Leveraging Cloud Features for Real-Time Insights
Explore the key aspects of real-time data streaming and analytics on cloud platforms, including architectures, integration strategies, and future trends.
November 6, 2024
· 16,138 Views · 4 Likes
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An Overview of Data Pipeline Architecture
Dive into how a data pipeline helps process enormous amounts of data, key components, various architecture options, and best practices for maximum benefits.
Updated June 3, 2024
· 16,585 Views · 5 Likes
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Data Processing in GCP With Apache Airflow and BigQuery
Efficient data processing is paramount. In this guide, we'll explore how to leverage Apache Airflow and BigQuery to create robust and scalable data pipelines.
March 20, 2024
· 16,243 Views · 5 Likes
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BigQuery DataFrames in Python
This article demonstrates how to effortlessly query, analyze, and write DataFrames in and out of BigQuery.
February 9, 2024
· 8,513 Views · 4 Likes

Trend Reports

Trend Report

Data Engineering

Over a decade ago, DZone welcomed the arrival of its first ever data-centric publication. Since then, the trends surrounding the data movement have held many titles — big data, data science, advanced analytics, business intelligence, data analytics, and quite a few more. Despite its varying vernacular, the purpose has remained the same: to build intelligent, data-driven systems. The industry has come a long way from organizing unstructured data and driving cultural acceptance to adopting today's modern data pipelines and embracing business intelligence capabilities.This year's Data Engineering Trend Report draws all former terminology, advancements, and discoveries into the larger picture, illustrating where we stand today along our unique, evolving data journeys. Within these pages, readers will find the keys to successfully build a foundation for fast and vast data intelligence across their organization. Our goal is for the contents of this report to help guide individual contributors and businesses alike as they strive for mastery of their data environments.

Data Engineering

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