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Snowflake SnowPro Advanced: Data Engineer Certification Exam Sample Questions (Q314-Q319):
NEW QUESTION # 314
A company reads data from customer databases that run on Amazon RDS. The databases contain many inconsistent fields. For example, a customer record field that iPnamed place_id in one database is named location_id in another database. The company needs to link customer records across different databases, even when customer record fields do not match.
Which solution will meet these requirements with the LEAST operational overhead?
- A. Create a provisioned Amazon EMR cluster to process and analyze data in the databases.
Connect to the Apache Zeppelin notebook. Use the FindMatches transform to find duplicate records in the data. - B. Create an AWS Glue crawler to craw the databases. Use Amazon SageMaker to construct Apache Spark ML pipelines to find duplicate records in the data.
- C. Create a provisioned Amazon EMR cluster to process and analyze data in the databases.Connect to the Apache Zeppelin notebook. Use an Apache Spark ML model to find duplicate records in the data. Evaluate and tune the model by evaluating the performance and results.
- D. Create an AWS Glue crawler to craw the databases. Use the FindMatches transform to find duplicate records in the data. Evaluate and tune the transform by evaluating the performance and results.
Answer: D
NEW QUESTION # 315
The COPY command supports several options for loading data files from a stage i.e.
I. By path
II. Specifying a list of specific files to load.
III. Using pattern matching to identify specific files by pattern.
IV. Organize files into logical paths that reflect a scheduling pattern.
Of the aforesaid options for identifying/specifying data files to load from a stage, which option in general is the fastest & best considerate?
- A. IV
- B. III
- C. II
- D. I
Answer: C
Explanation:
Explanation
Of the above options for identifying/specifying data files to load from a stage, providing a discrete list of files is generally the fastest; however, the FILES parameter supports a maximum of 1,000 files, meaning a COPY command executed with the FILES parameter can only load up to 1,000 files.
For example:
copy into load1 from @%load1/Snow1/ files=('mydata1.csv', 'mydata2.csv', 'mydata3.csv')
NEW QUESTION # 316
A university is developing an educational application that analyzes student essays. The application provides personalized feedback with accurate citations to the university's textbooks.
The application needs to process essays in multiple languages. Application responses must include direct references to specific sections in the course materials and must be in the student's selected language. Which solution will meet these requirements with the LEAST operational overhead?
- A. Build a custom vector database by using Amazon OpenSearch Serverless. Store textbook content as multilingual embeddings. Create an AWS Lambda function that queues the database when generating responses with Amazon Bedrock.
- B. Use Amazon SageMaker to host a custom-trained large language model (LLM) that has been fine-tuned on the university's textbooks to generate personalized feedback with citations.
- C. Create a knowledge base in Amazon Bedrock Knowledge Bases with the university's textbooks.
Configure a multilingual model to generate responses with source citations. - D. Use Amazon Comprehend to detect the language and key topics in the essays. Use Amazon Kendra to search for relevant textbook passages. Create an AWS Lambda function that formats the textbook passages into feedback.
Answer: C
Explanation:
Amazon Bedrock Knowledge Bases is the lowest-overhead solution because it provides a managed retrieval-augmented generation workflow over the university's textbooks and can return generated responses with citations to the source material. The RetrieveAndGenerate capability is designed to generate answers from retrieved textbook content and include source citations, which directly matches the requirement for accurate references to specific course materials. By choosing a multilingual model in Bedrock for generation, the application can respond in the student's selected language without building and operating a custom retrieval stack.
Reference:
https://docs.aws.amazon.com/bedrock/latest/userguide/knowledge-base.html
https://docs.aws.amazon.com/bedrock/latest/userguide/kb-test-retrieve-generate.html
https://docs.aws.amazon.com/bedrock/latest/userguide/kb-how-retrieval.html
NEW QUESTION # 317
A data engineer must orchestrate a data pipeline that consists of one AWS Lambda function and one AWS Glue job. The solution must integrate with AWS services.
Which solution will meet these requirements with the LEAST management overhead?
- A. Use an AWS Glue workflow to run the Lambda function and then the AWS Glue job.
- B. Use an Apache Airflow workflow that is deployed on an Amazon EC2 instance. Define a directed acyclic graph (DAG) in which the first task is to call the Lambda function and the second task is to call the AWS Glue job.
- C. Use an AWS Step Functions workflow that includes a state machine. Configure the state machine to run the Lambda function and then the AWS Glue job.
- D. Use an Apache Airflow workflow that is deployed on Amazon Elastic Kubernetes Service (Amazon EKS). Define a directed acyclic graph (DAG) in which the first task is to call the Lambda function and the second task is to call the AWS Glue job.
Answer: C
NEW QUESTION # 318
Alex, a Data Engineer with one of the Data analytics Organization, created the Materialized view over External tables to improve Data Reporting Experience.
Step 1: He created materialized view named DataReportMV
1.create or replace materialized view DataReportMV as
2.select Item_id, Item_price from Items;
Step 2: He joined a materialized view with a sales table as
1.create or replace view Revenue as
2.select m.item_id, sum(ifnull(s.quantity, 0)) as quantity,
3.sum(ifnull(quantity * (s.price - m.item_price), 0)) as profit
4.from DataReportMV as m left outer join sales as s on s.item_id = m.item_id
5.group by m.item_id;
Step 3: After 1 hour, he decided to temporarily suspend the use (and maintenance) of the DataRe-portMV materialized view for cost saving purpose.
alter materialized view DataReportMV suspend;
Please select what Alex is doing wrong here?
- A. Alex is doing everything correct.
- B. Materialized view on top of External tables is not supported feature.
- C. A materialized view, DataReportMV does not support Join operations, so Step 2 would be failed & he cannot proceed further.
- D. Once DataReportMV got suspended , any query on the top of the view will generate er-ror like:
Failure during expansion of view 'DATAREPORTMV': SQL compilation error: Material-ized view DataReportMV is invalid. - E. There is no command like suspend for temporarily suspension of Materialized views, Step 3 will give error like invalid Suspend command.
Answer: A
Explanation:
Explanation
All Steps will be executed successfully by Alex without any error.
NEW QUESTION # 319
......
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