DP 203 Dumps | DP 203 Real Exam Questions | Part 2

Summary

In this informative video, the host dives into the Azure DP203 certification, also known as Azure Data Engineer Associate, with a focus on the latest questions and answers. The video covers a range of topics, starting with Azure Stream Analytics and its windowing functions, moving on to designing folder structures for Azure Data Lake Storage Gen2, and discussing the process of ingesting data onto Azure's cloud data platform using ELT. The host also addresses the creation and use of external tables in Azure Synapse, the differences between structured and unstructured data, and the functionalities of temporal tables in Azure SQL Database. The video concludes with a discussion on the necessary roles for creating Azure Data Factory instances. Throughout, the host references Microsoft documentation to validate answers and provide a deeper understanding of the concepts discussed, making it an invaluable resource for those preparing for the DP203 exam.

Takeaways

• 📚 Start with the basics: The video is a part of a Q&A series on Azure DP203, focusing on the Azure Data Engineer Associate certification.
• 🔍 Validate answers with Microsoft Docs: The presenter uses Microsoft documentation to validate the provided answers, ensuring accuracy and reliability of the information.
• 💡 Understand Windowing Functions: For Azure Stream Analytics, hopping windowing function is used to output counts of records received in the last 5 minutes every minute.
• 📁 Folder Structure for ADLS Gen2: The recommended folder structure starts with the subject area, followed by the current year and month to support fast queries and simplified security.
• 📈 Sequential DDL Commands: For analyzing Twitter feed data in a dedicated SQL pool, the correct sequence of Transact-SQL DDL commands includes creating an external data source, file format, and then an external table as select.
• 🔑 Accessing External Tables: In Azure Data Explorer, to run a KQL query on an external table, use the 'external table' function.
• 🚀 ELT over ETL: For data ingestion onto a cloud data platform in Azure, the ELT (Extract, Load, and Transform) process is preferred.
• 🤖 Syntax Matters: In queries, ensure correct column names are referenced; otherwise, the query will return an error.
• 📊 Structured vs. Unstructured Data: Structured data defines data types at design time, while unstructured data defines data types at query time.
• ⏳ Temporal Tables: In Azure SQL Database, creating a temporal table with system versioning on automatically generates a history table to capture historical records.
• 👤 Azure Data Factory Permissions: To create Azure Data Factory instances, the user must be a member of the Contributor or Owner role, or an Administrator of the Azure subscription.

Q & A

What is the Azure certification being discussed in the video?

The video discusses the Azure DP203 certification, also known as Azure Data Engineer Associate.

What are the types of temporal windows supported by Azure Stream Analytics?

Azure Stream Analytics supports five types of temporal windows: tumbling, hopping, sliding, session, and snapshot.

Which windowing function should be used to output the count of records received from the last 5 minutes every minute?

The hopping windowing function should be used for this purpose.

What is the recommended folder structure to support fast queries and simplified folder security in Azure Data Lake Storage Gen2?

The recommended folder structure is one that starts with the subject area, followed by the current year, and then the current month.

What are the three Transact-SQL DDL commands that should be run in sequence to ensure Twitter feed data can be analyzed in a dedicated SQL pool?

The three commands are: CREATE EXTERNAL DATA SOURCE, CREATE EXTERNAL FILE FORMAT, and CREATE EXTERNAL TABLE AS SELECT.

How should a database user refer to an external table named 'ext_table' in Azure Data Explorer when running a KQL query?

The database user should use the 'EXTERNAL TABLE' function to refer to the 'ext_table'.

What data processing framework is typically used for ingesting data from an on-premises database into the Azure cloud?

The Extract, Load, and Transform (ELT) process is typically used for this purpose.

What will be returned by a query that attempts to select from a column named 'name' in a table where the actual column name is 'employee_name'?

The query will return an error due to the incorrect column name reference.

Is it true or false that in structured data you define the data type at query time?

False. In structured data, data types are defined at design time, not at query time.

What needs to be set to 'ON' to create a temporal table in Azure SQL Database?

System versioning needs to be set to 'ON'.

What roles or permissions are required to create Azure Data Factory instances?

The user account must be a member of the Contributor or Owner role, or an Administrator of the Azure subscription.

What does the acronym 'ELT' stand for and why is it used in the context of Azure cloud data ingestion?

ELT stands for Extract, Load, and Transform. It is used for efficiently moving large volumes of data into the Azure cloud, where data is first extracted and loaded into storage before being transformed.