Uploaded December 2024 | Updated September 2026, 2 hours ago
Discover 🔍 how food aggregators and quick-commerce platforms like Swiggy leverage the Snowflake to power their data pipelines! This hands-on 🛠️ tutorial starts with a high-level food order process flow, explores the OLTP source ER diagram for data analysis, and explains the 3-layer data warehouse architecture. Watch as we transform data flow requirements into implementation, create fact and dimension tables, and build an interactive Streamlit dashboard. Perfect for beginners or those curious about executing end-to-end data projects in Snowflake, this real life end to end data project walkthrough will demystify the process 🪜 step by step 🪜 using snowflake cloud data platform.
🏗️ Design Considerations: Explore the critical decisions behind crafting the data model and structuring the overall project architecture tailored for a food aggregator’s data pipeline.
📊 Data Flow: Follow the journey of data from loading and curation to transformation within Snowflake. Gain insights into the step-by-step process for ensuring data quality and integrity while leveraging Snowflake to maximize efficiency and streamline the pipeline.
Once you complete this end to end real life food aggregator based data engineering project (ETL or ELT) using snowflake, you would be able answer of following questions
🤔 How to load data using snowflake's snowsight data loading feature without any tool dependency
🤔 How to load delta data set and let is go through the data pipeline?
🤔 How to use $ notation to query stage file?
🤔 How to run copy command to load CSV files into tables?
🤔 How to design different layers & fact/dimension tables?
🤔 How to see the KPI and data insight using Streamlit?
🚀🚀 SQL Scripts & Sample Data Files
medium.com/@data-engineering-simplified 3f1af55005bf
🚀🚀 Data Engineering Simplified - Social Handlers 🚀🚀
instagram.com/learn_dataengineering
medium.com/@data-engineering-simplified
linkedin.com/company/data-engineering-simplified
https://x.com/everyday_data
🚀🚀 Snowflake Udemy Course By DES For Professional Learning 🚀🚀
✅ udemy.com/course/snowflake-complete-end-to-end-data-project-hands-on-guide
✅ udemy.com/course/snowflake-dynamic-table-masterclass-e2e-data-pipeline
✅ udemy.com/course/automatic-data-ingestion-using-snowflake-snowpark-python-api
✅ udemy.com/course/snowpark-python-ingest-json-data-automatically-in-snowflake
🚀🚀 Chapters
--------------------------
📖 00:00:00 Introduction
📖 00:05:20 High Level Architecture
📖 00:05:51 Welcome Note
📖 00:08:09 Source Data & ER Diagram
📖 00:15:04 CSV File Analysis
📖 00:17:32 E2E Design Approach
📖 00:20:28 DB + Schema Creation
📖 00:24:27 Data Loading
📖 00:35:41 Location Dimension
📖 01:02:42 Invalid Location Data
📖 01:07:18 Restaurant Dimension
📖 01:20:43 Customer Dimension
📖 01:27:26 Customer Address Dimension
📖 01:30:25 Menu Dimension
📖 01:34:26 Delivery Agent Dimension
📖 01:39:01 Delivery Entity
📖 01:41:33 Order Entity
📖 01:44:26 Order Item Entity
📖 01:46:45 Date Dimension
📖 01:48:58 Fact Table
📖 01:53:04 Snowsight Dashboard
📖 01:54:09 Data Lineage
📖 01:55:24 Large Volume Data Processing
📖 01:58:00 Orchestration Approaches
📖 02:01:12 Thank you note
#snowflake
#snowflaketutorial
#snowflakenotebooks
#dataengineeringsimplifed
#dataengineering
#dataengineeringessentials
#clouddatawarehouse
Disclaimer: All snowflake-related learning materials and tutorial videos published in this channel are the personal opinions of the data engineering simplified team and they're neither authorized by nor associated with Snowflake, Inc.
Discover 🔍 how food aggregators and quick-commerce platforms like Swiggy leverage the Snowflake to power their data pipelines! This hands-on 🛠️ tutorial starts with a high-level food order process flow, explores the OLTP source ER diagram for data analysis, and explains the 3-layer data warehouse architecture. Watch as we transform data flow requirements into implementation, create fact and dimension tables, and build an interactive Streamlit dashboard. Perfect for beginners or those curious about executing end-to-end data projects in Snowflake, this real life end to end data project walkthrough will demystify the process 🪜 step by step 🪜 using snowflake cloud data platform.
🏗️ Design Considerations: Explore the critical decisions behind crafting the data model and structuring the overall project architecture tailored for a food aggregator’s data pipeline.
📊 Data Flow: Follow the journey of data from loading and curation to transformation within Snowflake. Gain insights into the step-by-step process for ensuring data quality and integrity while leveraging Snowflake to maximize efficiency and streamline the pipeline.
Once you complete this end to end real life food aggregator based data engineering project (ETL or ELT) using snowflake, you would be able answer of following questions
🤔 How to load data using snowflake's snowsight data loading feature without any tool dependency
🤔 How to load delta data set and let is go through the data pipeline?
🤔 How to use $ notation to query stage file?
🤔 How to run copy command to load CSV files into tables?
🤔 How to design different layers & fact/dimension tables?
🤔 How to see the KPI and data insight using Streamlit?
🚀🚀 SQL Scripts & Sample Data Files
medium.com/@data-engineering-simplified 3f1af55005bf
🚀🚀 Data Engineering Simplified - Social Handlers 🚀🚀
instagram.com/learn_dataengineering
medium.com/@data-engineering-simplified
linkedin.com/company/data-engineering-simplified
https://x.com/everyday_data
🚀🚀 Snowflake Udemy Course By DES For Professional Learning 🚀🚀
✅ udemy.com/course/snowflake-complete-end-to-end-data-project-hands-on-guide
✅ udemy.com/course/snowflake-dynamic-table-masterclass-e2e-data-pipeline
✅ udemy.com/course/automatic-data-ingestion-using-snowflake-snowpark-python-api
✅ udemy.com/course/snowpark-python-ingest-json-data-automatically-in-snowflake
🚀🚀 Chapters
--------------------------
📖 00:00:00 Introduction
📖 00:05:20 High Level Architecture
📖 00:05:51 Welcome Note
📖 00:08:09 Source Data & ER Diagram
📖 00:15:04 CSV File Analysis
📖 00:17:32 E2E Design Approach
📖 00:20:28 DB + Schema Creation
📖 00:24:27 Data Loading
📖 00:35:41 Location Dimension
📖 01:02:42 Invalid Location Data
📖 01:07:18 Restaurant Dimension
📖 01:20:43 Customer Dimension
📖 01:27:26 Customer Address Dimension
📖 01:30:25 Menu Dimension
📖 01:34:26 Delivery Agent Dimension
📖 01:39:01 Delivery Entity
📖 01:41:33 Order Entity
📖 01:44:26 Order Item Entity
📖 01:46:45 Date Dimension
📖 01:48:58 Fact Table
📖 01:53:04 Snowsight Dashboard
📖 01:54:09 Data Lineage
📖 01:55:24 Large Volume Data Processing
📖 01:58:00 Orchestration Approaches
📖 02:01:12 Thank you note
#snowflake
#snowflaketutorial
#snowflakenotebooks
#dataengineeringsimplifed
#dataengineering
#dataengineeringessentials
#clouddatawarehouse
Disclaimer: All snowflake-related learning materials and tutorial videos published in this channel are the personal opinions of the data engineering simplified team and they're neither authorized by nor associated with Snowflake, Inc.
