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Snowflake DEA-C01 Exam Syllabus Topics:

Section	Objectives
Topic 1: Data Engineering Fundamentals on Snowflake	- Data ingestion concepts 1. Batch loading strategies 2. Continuous ingestion concepts - Snowflake architecture for data engineering 1. Virtual warehouses and compute scaling 2. Storage and compute separation
Topic 2: Performance Optimization	- Query performance tuning 1. Clustering and micro-partitions 2. Caching mechanisms - Warehouse optimization 1. Concurrency management 2. Scaling strategies
Topic 3: Data Loading and Integration	- Bulk data loading 1. COPY INTO command usage 2. File format handling - Snowpipe and continuous ingestion 1. Automated ingestion workflows 2. Event-driven loading
Topic 4: Security, Governance, and Data Sharing	- Data governance 1. Data masking policies 2. Secure data sharing concepts - Access control 1. Role-based access control (RBAC) 2. Object-level permissions
Topic 5: Data Pipelines and Transformation	- Streams and Tasks 1. Change Data Capture (CDC) with Streams 2. Automating pipelines with Tasks - ETL/ELT design patterns in Snowflake 1. Data orchestration concepts 2. Staging and transformation layers
Topic 6: Semi-Structured and Advanced Data Handling	- Semi-structured data processing 1. VARIANT data type usage 2. JSON, Avro, Parquet handling - Advanced transformation techniques 1. Complex transformations in SQL 2. Flattening nested data

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Snowflake SnowPro Advanced: Data Engineer Certification Exam Sample Questions (Q360-Q365):

NEW QUESTION # 360
A company built a data lake and a data warehouse on AWS. The company wants to implement a data catalog to enhance the current data storage solutions. The company wants to have the capability to add business metadata and glossary information to the data catalog for every asset.
Which solution will meet these requirements with the LEAST operational overhead?

A. Use Amazon OpenSearch Service. Create an index for the business glossary. Create a second index for the business metadata. Use the OpenSearch Service dashboard to access the metadata.
B. Use Amazon DataZone. Create the business glossaries. Create metadata forms. Use the Amazon DataZone data portal to access the metadata.
C. Use AWS Glue Catalog. Create a user table for the business glossary. Use the AWS Glue API to change table properties to add business metadata. Create a web application to access the metadata.
D. Use an Apache Hive metastore. Create a user table for the business glossary. Use the ALTER TABLE command to change table properties to add business metadata. Create a web application to access the metadata.

Answer: B

Explanation:
Amazon DataZone provides a fully managed data catalog and governance service with built-in support for business glossaries, custom metadata forms, and a user-friendly data portal. You can onboard your existing data assets, define glossaries, and capture business metadata without building or maintaining custom tables, APIs, or applications, minimizing operational overhead.

NEW QUESTION # 361
A company receives marketing campaign data from a vendor. The company ingests the data into an Amazon S3 bucket every 40 to 60 minutes. The data is in CSV format. File sizes are between
100 KB and 300 KB.
A data engineer needs to set-up an extract, transform, and load (ETL) pipeline to upload the content of each file to Amazon Redshift.
Which solution will meet these requirements with the LEAST operational overhead?

A. Use Amazon Redshift Spectrum to query the S3 bucket. Configure an AWS Glue Crawler for the S3 bucket to update metadata in an AWS Glue Data Catalog.
B. Create an Amazon Data Firehose stream. Configure the stream to use an AWS Lambda function as a source to pull data from the S3 bucket. Set Amazon Redshift as the destination.
C. Create an AWS Lambda function that connects to Amazon Redshift and runs a COPY command.
Use Amazon EventBridge to invoke the Lambda function based on an Amazon S3 upload trigger.
D. Creates an AWS Database Migration Service (AWS DMS) task. Specify an appropriate data schema to migrate. Specify the appropriate type of migration to use.

Answer: C

Explanation:
Configuring your S3 bucket to emit "Object Created" events into EventBridge and using a rule to invoke a lightweight Lambda function lets you automatically run a Redshift COPY for each new CSV. This serverless, event-driven pattern requires no continuously running infrastructure and has minimal operational overhead.

NEW QUESTION # 362
A global ecommerce company processes customer transactions, inventory updates, and user activity logs across multiple AWS services. The company needs a scalable, fully managed, and event-driven orchestration solution to coordinate complex extract, transform, and load (ETL) workflows. The solution must use AWS Glue and Amazon EMR to process data. The data will be stored in Amazon Redshift and Amazon S3. The solution must support dependency management, automated retries, and data pipeline monitoring. Which solution will meet these requirements?

A. Use AWS Step Functions to define an express workflow that invokes the data transformation and loading tasks across Amazon EMR and AWS Glue.
B. Create an AWS Lambda function that runs each step of the workflow. Create an Amazon EventBridge scheduled rule to invoke the function every day.
C. Use Apache Airflow on Amazon Managed Workflows for Apache Airflow (Amazon MWAA) to create Directed Acyclic Graphs (DAGs) to manage ETL workflows.
D. Create AWS Lambda functions for each step of the workflow Configure Amazon EventBridge to invoke AWS Glue jobs. Configure the Lambda functions to process and move data through the pipeline.

Answer: C

Explanation:
Amazon Managed Workflows for Apache Airflow is a fully managed orchestration service built specifically for coordinating complex ETL workflows with dependencies, retries, scheduling, and monitoring. Airflow DAGs can natively orchestrate AWS Glue and Amazon EMR jobs and manage data movement into Amazon Redshift and Amazon S3, making it the best fit for a scalable, event-driven ETL orchestration requirement.

NEW QUESTION # 363
A company stores a large dataset in an Amazon S3 bucket. A data engineer frequently runs complex queries on the dataset by using Amazon Athena. The data engineer needs to optimize query performance and optimize costs for queries that are run multiple times with the same parameters. Which solution will meet these requirements?

A. Use Amazon EMR to pre-process the data before running Athena queries.
B. Use Amazon Redshift Spectrum to query the data in Amazon S3.
C. Convert the dataset to JSON format before running Athena queries.
D. Configure query result reuse settings in the Athena workgroup.

Answer: D

Explanation:
Athena query result reuse allows repeated queries with the same text and parameters to return previously computed results instead of scanning the source data again. This improves performance for repeated queries and reduces query costs by avoiding unnecessary data scans.

NEW QUESTION # 364
Data Engineer wants to analyze query performance & looking out for profiling information, He went to Query/Operator Details also called Profile Overview of Query Profile Interface & searching for statistics attributes around I/O. Which of the following information he can't get from there?

A. Bytes sent over the wireframe - amount of data sent over the wireframe
B. External bytes scanned - bytes read from an external object, e.g. a stage.
C. Percentage scanned from cache - the percentage of data scanned from the local disk cache.
D. Bytes written - bytes written (e.g. when loading into a table).
E. Bytes read from result - bytes read from the result object.

Answer: A

Explanation:
Explanation
To help you analyze query performance, Query/Operator Details panel also called Profile overview panel provides two classes of profiling information:
Execution time, broken down into categories
Detailed statistics
Apart from Option a Bytes sent over the wireframe - amount of data sent over the wireframe , Rest of the Statistics Information provided by Query/Operator details in the Query Profile Inter-face.
To Know More about the Query/Operator Details options , please refer the link:
https://docs.snowflake.com/en/user-guide/ui-query-profile#query-operator-details

NEW QUESTION # 365
......

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