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Snowflake DEA-C01 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Performance Optimization & Scalability15%- Optimize warehouses, clustering, partitioning, and query performance
- Design scalable compute and storage solutions
- Monitor and tune workloads and resource usage
Topic 2: Data Governance, Security & Sharing10%- Apply access control, masking, encryption, and compliance
- Track lineage, audit, and maintain data integrity
- Share data securely across accounts and platforms
Topic 3: Data Pipeline Orchestration & Automation20%- Integrate with external orchestration tools
- Build, schedule, monitor, and manage workflows
- Error handling, retry logic, and dependency management
Topic 4: Data Transformation & Processing30%- Implement data quality, validation, and schema evolution
- Work with semi-structured and unstructured data
- Use streams, tasks, dynamic tables for pipelines and CDC
- Design and implement transformations: SQL, stored procedures, user-defined functions
Topic 5: Data Ingestion25%- Use COPY INTO, external tables, Snowpipe, Snowpipe Streaming
- Ingest from various sources: cloud storage, on-premises, APIs, data lakes
- Handle file formats, compression, encoding, and schema detection

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Snowflake SnowPro Advanced: Data Engineer Certification Exam Sample Questions (Q246-Q251):

NEW QUESTION # 246
A stream called TRANSACTIONS_STM is created on top of a transactions table in a continuous pipeline running in Snowflake. After a couple of months, the TRANSACTIONS table is renamed transactiok3_raw to comply with new naming standards What will happen to the TRANSACTIONS _STM object?

Answer: C

Explanation:
Explanation
A stream is a Snowflake object that records the history of changes made to a table. A stream is associated with a specific table at the time of creation, and it cannot be altered to point to a different table later. Therefore, if the source table is renamed, the stream will become stale and will need to be re-created with the new table name. The other options are not correct because:
TRANSACTIONS _STM will not keep working as expected, as it will lose track of the changes made to the renamed table.
TRANSACTIONS _STM will not be automatically renamed TRANSACTIONS _RAW_STM, as streams do not inherit the name changes of their source tables.
Reading from the transactions_stm stream will not succeed for some time after the expected STALE_TIME, as streams do not have a STALE_TIME property.


NEW QUESTION # 247
How can the following relational data be transformed into semi-structured data using the LEAST amount of operational overhead?

Answer: A

Explanation:
Explanation
This option is the best way to transform relational data into semi-structured data using the least amount of operational overhead. The OBJECT_CONSTRUCT function takes a variable number of key-value pairs as arguments and returns a Snowflake object, which is a variant type that can store JSON data. The function can be used to convert each row of relational data into a JSON object with the column names as keys and the column values as values.


NEW QUESTION # 248
Tasks may optionally use table streams to provide a convenient way to continuously process new or changed data. A task can transform new or changed rows that a stream surfaces. Each time a task is scheduled to run, it can verify whether a stream contains change data for a table and either consume the change data or skip the current run if no change data exists. Which System Function can be used by Data engineer to verify whether a stream contains changed data for a table?

Answer: C

Explanation:
Explanation
SYSTEM$STREAM_HAS_DATA
Indicates whether a specified stream contains change data capture (CDC) records.


NEW QUESTION # 249
A company uses an Amazon S3 bucket to integrate multiple data sources into a central data lake.
The company needs to perform multiple transformations and data cleaning processes on the data to make the data accessible to business partners.
The company needs a solution that will give multiple business partners the ability to run SQL queries on the central data lake during normal business hours.
Which solution will meet these requirements MOST cost-effectively?

Answer: C

Explanation:
AWS Glue Flex Jobs provide discounted, off-hours batch ETL to transform S3 data, and Amazon Redshift Serverless offers on-demand SQL access during business hours without paying for idle clusters minimizing cost and operations.


NEW QUESTION # 250
Jackie, a Data engineer advised to his data team members about one of the Role highlighting fol-lows points:
1. Avoid Using the <?> Role for Automated Scripts
2. Avoid Using the <?> Role to Create Objects
Which System defined or Custom Role She is mentioning?

Answer: D


NEW QUESTION # 251
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