Data Integration Simplified: Discover Airbyte’s Magic in Just 15 Minutes!

Welcome, data enthusiasts! In today's video, we're diving deep into the world of data integration, focusing on ELT (Extract, Load, Transform), comparing it with ETL, and showcasing the magic of Airbyte—a powerful tool for simplifying your data workflows.

📊 Key Topics Covered:
- Understand the ELT process and its advantages.
- Explore the differences between ETL and ELT.
- Brief insight into the modern data stack.
- Unveiling Airbyte's core concepts for seamless data integration.
- Live demonstration: Connecting PostgreSQL to Redshift, MongoDB to Redshift, and more!
- Concluding thoughts on Airbyte's transformative power in fintech data integration.

🚀 Why Watch?
Discover how Airbyte simplifies the complex task of consolidating fintech data sources into Amazon Redshift, enabling informed decision-making and operational efficiency. This is just the beginning – Airbyte's flexibility and extensive connectors open doors to endless possibilities across industries!

👉 Explore Further:
If you're in the realm of data integration or a fintech professional eager to enhance your data infrastructure, dive into Airbyte! The vibrant open-source community ensures constant evolution with new features and improvements.

Timestamps:
00:00 Introduction
00:24 ETL v/s ELT
02:14 What is Airbyte?
02:43 Airbyte core concepts and terminologies
04:37 Airbyte live demo
05:43 How to set up PostgreSQL in Airbyte?
06:50 How to set up MongoDB in Airbyte?
07:25 How to set up Redshift in Airbyte?
09:26 How to connect from source to destination in Airbyte?

Thank you for watching! If you found this video helpful, don't forget to like, share, and subscribe for more insights into the world of data integration and technology. Stay tuned for our upcoming videos! 🌐

#Airbyte #Analytics #DataEngineering #DataIntegration #ELTvsETL #AirbyteMagic #DataPipelines #Aptuz #FintechTech #ModernDataStack

[Naman.Paliwal_RIL]

I have mutilple .gz files (which gives csv files on being extracted) in my S3 bucket. I want to make a pipeline in airbyte that take each .gz file, unzip it, extract the csv from it, transform it and load it to a specific table in my schema. Now, lets say there are 23 .gz file and my target table is my_table in my_schema in redshift. How, can I set a target table? I can see the target schema option but target table is not visible, please help me out what should be my approach in this use case?