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Azure Databricks for data engineers and data developers
Data engineering is about 70% of any data pipeline today, and without having the experience to implement a data engineering pipeline well, there is no value to be accumulated from your data. In this session we discuss the best practices and demonstrate how a data engineer can develop and orchestrate the big data pipeline, including: data ingestion and orchestration using Azure Data Factory; data curation, cleansing and transformation using Azure Databricks; data loading into Azure SQL Data Warehouse for serving your BI tools. Learn how to effectively do the ETL/ELT process combined with advanced capabilities such as monitoring the jobs, getting alerts, jobs retrial, set permissions, and much more.
Learn how Devon Energy leverages Azure Databricks to build predictive machine learning and AI models at scale