Learn the power of the Lakehouse In today's data-filled world, we need tools that allow us to be as data-driven as possible. This course guides you from start to finish on how the Databricks Lakehouse Platform provides a single, scalable, and performant platform for your data processes. Working through a real-world dataset will teach you how to accomplish various tasks within the Databricks platform. You'll start the course by learning how to administer the Databricks platform and ensuring your environment is set up securely.
Practice scalable data engineering After setting up your workspace, you will learn how to create powerful data pipelines using Databricks. You will apply different transformations to the dataset, moving it from Bronze to Silver and then Gold in a Medallion architecture. You will learn how Databricks clusters provide readily available compute power and scalability. You will set up an end-to-end Databricks Workflow to automate your entire data pipeline.
Use the Lakehouse as your data warehouse A key part of the Lakehouse architecture is that you can query your data storage like a traditional data warehouse. In this section, you will learn how Databricks SQL gives you the data warehousing performance you want on top of your data lake. You will learn how to create queries using standard ANSI SQL, and use those results to create ad-hoc dashboards against your entire dataset.
Implement governed data science and machine learning Finally, you will learn how Databricks provides a complete set of tools for data science and machine learning use cases. You will learn to track and evaluate your models using the fully integrated MLFlow framework for MLOps. You will learn how the Feature Store and Model Registry simplify the process of creating production-quality machine-learning models. Finally, you will learn how to deploy and monitor your models using built-in model serving capabilities.
Introduction to DatabricksFree
Learn about the new lakehouse paradigm for your cloud data strategy and how the Databricks Lakehouse platform can modernize your data architecture. Understand the foundational components of the Databricks platform and how they all fit together.Introduction to the Databricks Lakehouse Platform50 xpWhy pick a Lakehouse?50 xpBenefits of the Databricks Lakehouse50 xpArchitectural Decisions100 xpCore features of the Databricks Lakehouse Platform50 xpWhy Delta?50 xpDatabricks for different personas50 xpCapabilities for each data persona100 xpAdministering a Databricks workspace50 xpManaging and adding users50 xpSetting up a Databricks workspace example50 xpControl Plane vs. Data Plane50 xpConfigure your Databricks workspace100 xp
Learn how to process, transform, and clean your data using Databricks functionality. Practice using capabilities such as the Delta storage format, Delta Live Tables, and Workflows together to create an end-to-end data pipeline.Getting started with Databricks50 xpData Explorer capabilities50 xpSetting up a notebook50 xpCluster configurations100 xpData Engineering foundations in Databricks50 xpDataFrames50 xpReading from a database50 xpWrite an external table100 xpData transformations in Databricks50 xpLoading in hosted files50 xpSelecting the right language100 xpData pipeline steps100 xpData orchestration in Databricks50 xpPossible automations in Databricks100 xpBenefits of Delta Live Tables50 xpEnd-to-end data pipeline example in Databricks50 xpData pipeline steps100 xp
Databricks SQL and Data Warehousing
Use the Databricks Lakehouse platform as your data warehousing solution for your Business Intelligence (BI) use cases. Use the built-in SQL-optimized capabilities within Databricks to create queries and dashboards on your data.Overview of Databricks SQL50 xpBenefits of Databricks SQL50 xpDatabricks SQL in the data workflow100 xpDatabricks SQL vs. other databases100 xpGetting started with Databricks SQL50 xpChoosing your SQL warehouse50 xpSQL Editor vs. notebooks50 xpCreating the usSales table100 xpDatabricks SQL queries and dashboards50 xpUnderstanding Databricks SQL assets50 xpUsing parameters in queries50 xpCreating a Databricks SQL Dashboard50 xpCreate a user review query100 xp
Databricks for Large-scale Applications and Machine Learning
Use Databricks to manage your Machine Learning pipelines with managed MLFlow. Follow the model development lifecycle from end-to-end with the Feature Store, Model Registry, and Model Serving Endpoints to create a robust MLOps platform in the lakehouse.Overview of Lakehouse AI50 xpLakehouse benefits to ML50 xpMLOps tasks in Databricks100 xpUsing Databricks for machine learning50 xpEDA in Databricks50 xpWhy the ML Runtime?50 xpExploring data in a notebook100 xpModel training with MLFlow in Databricks50 xpSingle node vs. multi node ML100 xpDatabricks for citizen data scientists50 xpUsing MLFlow for Tracking100 xpDeploying a model in Databricks50 xpModels and the Model Registry50 xpWhy Databricks for model deployment?50 xpExample end-to-end machine learning pipeline50 xpEnd-to-end ML pipeline100 xpWrap Up50 xp