Automated Lakeflow Declarative Pipeline | Delta Live Tables + Workflows | Databricks Project| Python
Автор: DataToCrunch
Загружено: 2025-09-15
Просмотров: 8127
Welcome back to DataToCrunch.
📌 In this project, I have utilized Databrick platform to create Automated Lakeflow Declarative Pipeline(DLT). In the initial part, I have covered the necessary theory to create this pipeline & workflow followed by the practical part.
Topics covered :
📂 Landing Layer – Auto Loader ingestion of customers & accounts data
🥉 Bronze Layer – Data cleaning with expectations & data quality checks
🥈 Silver Layer – Transformations, Slowly Changing Dimensions (SCD1 & SCD2)
🥇 Gold Layer – Business aggregations & materialized views for analytics
📊 BI & Reporting – Building dashboards powered by the Gold Layer
✅ Key concepts: backfilling, append flow, auto CDC, expectations, lineage, and governance
⚙️ How DLT + Workflows automate orchestration, improve reliability, and simplify operations
This project demonstrates how Databricks LakeFlow (DLT) makes data engineering pipelines declarative, scalable, and production-ready, while powering dashboards for real-time insights.
Dataset Available on https://github.com/RutujaKadam95/Auto...
🔖 TimeStamp:
Theory -
0:00:00 - Intro
0:00:29 - Difficulties Before Lakeflow Declarative Pipelines
0:02:52 - How problems were solved with lakeflow declarative pipeline
0:06:13 - Databricks Lakeflow Overview
0:11:03 - Jobs & Pipeline Databricks Platform Overview
0:15:59 - Lakeflow Connect - Data Ingestion
0:16:59 - Batch Processing & Streaming Processing
0:18:30 - Data Ingestion Ways( Create Table, Copy Into, Autoloader )
0:23:47 - Lakeflow Declarative Pipeline/ Delta Live Tables
0:26:18 - Datasets - Streaming Table, Materialized View, Temporary View
0:39:03 - Expectations
0:52:34 - Append Flow, Auto CDC, Apply Changes, Backfilling
1:09:31 - DLT - Databricks Platform Overview
1:25:49 - Workflows
1:32:09 - Workflows Databricks Platform Overview
1:48:41 - Project Overview
1:52:00 - Data Understanding
1:56:08 - Part part begins
1:59:36 - Data Ingestion
2:01:58 - DLT creation
2:07:15 - Bronze Work
3:03:59 - Silver Work
3:37:32 - Gold Work
3:47:51 - Dashboards
3:53:19 - Workflows
4:12:56 - Summary
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