Microsoft DP-700 prep: Fabric Data Engineer Associate

This course covers the content required for the Microsoft DP-700 "Fabric Data Engineer Associate" certification exam, using the Study Guide for "Implementing Analytics Solutions Using Microsoft Fabric".

This course is also useful for the following Microsoft Applied Skills:

APL-3008 "Implement a Real-Time Intelligence solution with Microsoft Fabric"

APL-3009 "Implement a lakehouse in Microsoft Fabric"

APL-3010 "Implement a data warehouse in Microsoft Fabric"

Please note: This course is not affiliated with, endorsed by, or sponsored by Microsoft.

What do students like you say about this course?

Kin says: "Thank you so much for this content, very helpful. I love the flow of how you explain things starting from the most simple scenario and add complexity gradually, and how you anticipate common questions and address them. I learned more from this than the official Microsoft instructors I got from my workplace... Very well done!"

David says: "Philip takes time to explain things on a basic level so a novice to the topic can start building knowledge from scratch, following it up by in-depth explanations and details. The practice activities are also a very nice touch!"

Warren says: "This course is absolutely phenomenal in preparation for the DP-700 but also learning if you have zero experience. Microsoft Fabric is quite a large platform, and the exam can be very broad. Phillip does an outstanding job of covering an incredible amount of content in an easy-to-understand manner. The practice activities are well thought out and actually quite helpful in applying what is being taught.

There are other resources out there, but this tops them all. Phillip is also incredibly responsive to any questions out there. I cannot understand why anyone would not give this course 5 stars."

What will you learn in this course?

• Following a quick look around Fabric, we will look at using Dataflow Gen2 and pipelines - ingesting and copying data, and scheduling and monitoring data pipeline runs.
• Next we'll manipulate data using PySpark and SQL in a notebook.
• We'll have a look at loading and saving data using notebooks.
• We'll then manipulating dataframes, by choosing which columns and rows to show.
• We'll then convert data types, aggregating and sorting dataframes,
• We will then be transforming data in a lakehouse, merging and joining data, together with identifying missing data or null values.
• We will then be improving notebook performance and automate notebooks, together with creating objects, such as shortcuts and file partitioning.
• Following this, we'll look at using a data warehouse - transforming data, creating an incremental data load, and managing and optimizing them.
• We'll then create an eventhouse, and find out how to transform data using KQL:
• We'll select, filter and aggregate data.
• We'll manipulate data using string, number, datetime and timespan functions.
• We'll end these sections by transforming data, merging and joining data and more.
• Finally, we will look at ingesting and transforming streaming data, including revising KQL knowledge from the DP-600 exam, workspace settings and monitoring.

No prior knowledge is assumed. We will start from the beginning for all languages and items, although any prior knowledge of PySpark, SQL or KQL is useful.

Once you have completed the course, you will have a good knowledge of using notebooks to manipulate data using PySpark. And with some practice and knowledge of some additional topics, you could even go for the official Microsoft certification DP-700 - wouldn't the "Microsoft Certified: Fabric Data Engineer Associate" certification look good on your CV or resume?

I hope to see you in the course - why not have a look at what you could learn?

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