Implementing a Data Analytics Solution with Azure Databricks (DP-3011)

Unlock the potential of Azure Databricks with our intermediate-level course designed for data professionals, including Data Engineers and Data Scientists. Dive into the realm of Apache Spark and master the utilization of powerful clusters on the Azure Databricks platform to tackle large-scale data engineering tasks in the cloud. Whether you're optimizing data pipelines, building machine learning models, or analyzing vast datasets, this course equips you with the skills and insights needed to excel in today's data-driven world. Implementing a Data Analytics Solution with Azure Databricks (DP-3011) Benefits In this course, you will: Gain hands-on experience in harnessing many of the capabilities of Azure Databricks for data engineering tasks.  Enhance your proficiency in Apache Spark, a leading big data processing framework, and leverage it effectively in the cloud environment.  Learn best practices for optimizing data workflows and pipelines, ensuring efficiency and scalability.  Acquire the skills to build and deploy advanced machine learning models using Azure Databricks, empowering you to extract actionable insights from your data.  Training Prerequisites None. Certification Information Helps prepare for Exam DP-203: Data Engineering on Microsoft Azure  Implementing a Data Analytics Solution with Azure Databricks (DP-3011) Training Outline Explore Azure Databricks Get started with Azure Databricks Identify Azure Databricks workloads Understand key concepts Use Apache Spark in Azure Databricks Get to know Spark Create a Spark cluster Use Spark in notebooks Use Spark to work with data files Visualize data Use Delta Lake in Azure Databricks Get Started with Delta Lake Create Delta Lake tables Create and query catalog tables Use Delta Lake for streaming data Use SQL Warehouses in Azure Databricks Get started with SQL Warehouses Create databases and tables Create queries and dashboards Run Azure Databricks Notebooks with Azure Data Factory Understand Azure Databricks notebooks and pipelines Create a linked service for Azure Databricks Use a Notebook activity in a pipeline Use parameters in a notebook