Connecting to SQL Server from Databricks

Course Overview

What does this course tell?
(Please note that the following overview content is from the original platform)

This course covers the steps involved in setting up a SQL Server instance and a Databricks workspace in the same virtual network, and querying the database from a notebook.
Databricks is a versatile and powerful data platform which can help us perform a lot of processing, analysis and machine learning tasks. But it often needs to source its data from external storage systems, such as relational databases. In this course, Connecting to SQL Server from Databricks, you'll learn how the data in a SQL Server database can be accessed from a Databricks workspace. First, you'll explore provisioning a Databricks workspace in a custom virtual network. Next, you'll discover a number of connection rules to ensure that Databricks and SQL server can communicate with each other, and also enable connections to the database from a local SQL client. Finally, you'll learn how to query a table in the SQL Server database from a notebook in our Databricks workspace. Once you complete this course, you will become aware of the infrastructure set-up needed to ensure that two popular data platforms - Databricks and SQL Server - are able to communicate with one another, and can implement such a link in your own environment.What can you get from this course?
We consider the value of this course from multiple aspects, and finally summarize it for you from three aspects: personal skills, career development, and further study:
(Kindly be aware that our content is optimized by AI tools while also undergoing moderation carefully from our editorial staff.)
What skills and knowledge will you acquire during this course?
By taking this course, learners will acquire the skills and knowledge to set up a SQL Server instance and a Databricks workspace in the same virtual network, and query the database from a notebook. They will understand the connection rules needed to ensure that Databricks and SQL server can communicate with each other, and also enable connections to the database from a local SQL client. Additionally, learners will gain the knowledge of how to query a table in the SQL Server database from a notebook in the Databricks workspace. Finally, they will be able to implement the infrastructure set-up needed to ensure that two popular data platforms - Databricks and SQL Server - are able to communicate with one another.

How does this course contribute to professional growth?
This course contributes to professional growth by providing learners with the knowledge and skills needed to set up a SQL Server instance and a Databricks workspace in the same virtual network, and query the database from a notebook. Learners will gain an understanding of the connection rules needed to ensure that Databricks and SQL server can communicate with each other, and also enable connections to the database from a local SQL client. Additionally, learners will be able to implement the infrastructure set-up needed to ensure that two popular data platforms - Databricks and SQL Server - are able to communicate with one another. This knowledge can be applied to a variety of scenarios, such as data analysis, machine learning, and data engineering, and can be used to pursue a career in data science.

Is this course suitable for preparing further education?
This course is suitable for preparing further education, as it provides learners with the knowledge and skills needed to set up a SQL Server instance and a Databricks workspace in the same virtual network, and query the database from a notebook. Additionally, learners will gain the knowledge of how to query a table in the SQL Server database from a notebook in the Databricks workspace. This knowledge can be applied to a variety of scenarios, such as data analysis, machine learning, and data engineering, which are all necessary skills for pursuing a career in data science. Furthermore, this course provides learners with the necessary skills to work with data-driven technologies, which can be applied to a variety of degree programs, such as a Bachelor of Science in Computer Science, Master of Science in Data Science, Master of Science in Artificial Intelligence, and Doctor of Philosophy in Data Science.