📰 End-to-End News Data Pipeline | Databricks, PySpark, Delta Lake, Hive, and Sentiment Analysis

Описание: In this video, I walk you through a full-scale data pipeline for processing and analyzing news articles using the modern medallion architecture (Bronze → Silver → Gold). The pipeline is built on Databricks and utilizes PySpark, Delta Lake, and Hive Metastore, with integrated sentiment analysis using TextBlob and robust data quality validation mechanisms.

🔧 Technologies Used:

Apache Spark (PySpark)

Delta Lake (ACID Transactions)

Azure Data Lake Gen2 (Storage)

Hive Metastore / Unity Catalog (Metadata Management)

TextBlob (NLP Sentiment Analysis)

Databricks (ETL Orchestration)

📌 What You'll Learn:

How to ingest data from APIs and store in Delta format

Dynamic data quality checks and quarantining bad records

Enriching data with NLP sentiment scores

Building star-schema data models with fact/dim tables

Writing clean data to Hive and exposing it for BI

📁 GitHub Repo:
👉 https://github.com/david-ikenna-ezeki...


📌 Referenced Video
How to Provision the Medallion Architecture on Azure ADLS using Terraform:    • How to Provision the Medallion Architectur...  

Medallion Architecture Explained: From Raw Data to Business Insights:    • Medallion Architecture Explained: From Raw...  

How to Create Azure Key Vault and Connect with Databricks:    • How to Create Azure Key Vault and Connect ...  

How to Design a Data Model Using Python and SQLite:    • How to Design a Data Model Using Python an...  

How to Connect to Databricks from PowerBI:    • How to Connect to Databricks from PowerBI  


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