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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.

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