Join our End-to-End Data Pipeline Workshop and take your data engineering skills to the next level! This hands-on technical session will guide you through building a modern data pipeline using Azure Data Lake Storage (ADLS), Databricks, and Snowflake. You’ll learn how to seamlessly ingest, process, and store data, creating a scalable pipeline from raw storage to analytics-ready data.

Key Topics Include:

• Setting up and Configuring ADLS for Data Ingestion:

Learn how to configure Azure Data Lake Storage and ingest raw data for structured, semi-structured, and unstructured workflows.

• Processing and Transforming Data in Databricks:

Use Databricks and Apache Spark to clean, transform, and prepare data using PySpark and SQL.

• Integrating Databricks with Snowflake for Data Storage:

Configure the Snowflake Spark Connector to load processed data into Snowflake for analytics.

• Optimizing the Pipeline for Performance and Scalability:

Explore best practices for building cost-efficient and high-performance pipelines, ensuring seamless integration.

By the end of this workshop, you’ll have mastered the skills required to build scalable, production-ready data pipelines that connect cloud storage, processing platforms, and modern data warehouses. Perfect for data engineers, data analysts, and technical professionals seeking to enhance their skills in data pipeline development.

Let’s build the future of data workflows together!