SnowPro Advanced: Data Engineer Certification Guide
Preparation, checks and hints needed to clear SnowPro Advanced: Data Engineer Certification in your 1st attempt
SnowPro Advanced: Data Engineer Certification sure is intense exam and though than anticipated. In comparison to Architect exam, more hands on is needed as almost every question is scenario based in combination of different topics, with just a handful of direct questions present.
Suggest you to take SnowPro Advanced: Architect Certification before taking up Data Engineer certification and do revise if its done long back — https://snowflakewiki.medium.com/snowflake-get-self-started-6859d4f2112c
Important for Preparation -
Visit the SnowPro Advanced: Data Engineer Exam Guide — https://learn.snowflake.com/courses/course-v1:snowflake+CERT-SPC-GUIDE+A/about?_ga=2.234095838.1541219588.1647157808-1471695939.1646832664
Give the special attention to the following. (Note — It can get changed from time to time) -
Total Number of Questions
Question Types
Time Limit
Then go through each and every topic that is mentioned in the Exam Domain section in detail (Note — It can get changed from time to time).
Download the exam study guide and revise the topics listed -
Important Topics -
As questions are mostly scenario based, have abundant amount of hands on practice based on the following topics along with pointers mentioned below going through the links provided.
Performance Considerations: Clustering, Materialized Views, Search Optimization
Have thorough understanding of clustering concept, materialized views and search optimization with query syntaxes. You will have questions in combination as well. Understand the use cases and precedence in different scenarios.
How and when to choose a clustering key?
How to define and drop clustering key?
What is clustering depth and overlap depth?
How do you view/monitor clustering information?
When to define MVs?
How and when to define search optimization?
https://docs.snowflake.com/en/user-guide/tables-clustering-micropartitions.html
https://docs.snowflake.com/en/user-guide/views-materialized.html
COPY INTO parameters and File Format options
Where and how many ways can we define the file formats and precedence of diff ways?
Use case of VALIDATION_MODE with COPY_OPTIONS
Snowpipe
How to create a Snowpipe?
How to track and validate data loads using Snowpipe?
Use cases related to Snowpipe
Streams & Tasks
How to create stream?
How to know if stream has data?
How to consume the stream data within transitional processing?
How and when stream data becomes stale?
How to create task and use it real time?
How to resume and suspend task?
How to use streams within tasks?
What privileges' are needed to create and execute the task?
Time Travel & Cloning
There are scenarios on time travel, retention period, data cloning
How to query historical data syntax? (Using timestamp, offset, statement)
At what object level time travel retention period can be changed and how it impacts the data recovery?
What happens when different objects data retention time in days is altered?
Data Sharing
In this exam, questions on share are mostly integrated with other topics.
Can we clone share objects?
How to enable change data capture on share object?
Stored Procedures, UDF, Semi structed data
How the transactional processing happens using stored procedures? (Begin, Commit, Rollback)
How to create UDF and use cases?
How to query JSON data?
How to handle NULL’s in JSON data?
https://docs.snowflake.com/en/sql-reference/transactions.html
External Tables and External Functions
External Function with API Integration and its rules.
https://docs.snowflake.com/en/sql-reference/external-functions-introduction.html
Exam Day Tips -
- Don’t get stuck and flag the questions you may be confused during the exam and proceed further. Many a case, you can get hint in the following questions asked during the certification.
- If you are left with time, do revisit all the questions and cross check your answers (especially the multiple choice and scenario based ones)
Good luck for exam and get Snowed at Data Engineer Level!
References: https://www.snowflake.com/
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