実用的なDEA-C01学習教材試験-試験の準備方法-ハイパスレートのDEA-C01サンプル問題集

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これは、今後のDEA-C01テストのために有効な試験準備資料を購入する良い方法です。適切な選択により、半分の労力で2倍の結果が得られます。適切な試験準備により、明確な方向性が示され、効率的な準備ができます。 DEA-C01試験の準備は正しい方向を示すだけでなく、実際の試験問題のほとんどをカバーできるため、試験の内容を事前に知ることができます。 Snowflake DEA-C01試験準備の質問と回答をマスターし、試験気分を積極的に調整することもできます。

Snowflake DEA-C01 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Data Ingestion	25%	- Ingest from various sources: cloud storage, on-premises, APIs, data lakes - Use COPY INTO, external tables, Snowpipe, Snowpipe Streaming - Handle file formats, compression, encoding, and schema detection
Topic 2: Data Governance, Security & Sharing	10%	- Apply access control, masking, encryption, and compliance - Track lineage, audit, and maintain data integrity - Share data securely across accounts and platforms
Topic 3: Data Transformation & Processing	30%	- Work with semi-structured and unstructured data - Implement data quality, validation, and schema evolution - Use streams, tasks, dynamic tables for pipelines and CDC - Design and implement transformations: SQL, stored procedures, user-defined functions
Topic 4: Performance Optimization & Scalability	15%	- Monitor and tune workloads and resource usage - Design scalable compute and storage solutions - Optimize warehouses, clustering, partitioning, and query performance
Topic 5: Data Pipeline Orchestration & Automation	20%	- Integrate with external orchestration tools - Build, schedule, monitor, and manage workflows - Error handling, retry logic, and dependency management

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DEA-C01サンプル問題集、DEA-C01クラムメディア

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Snowflake SnowPro Advanced: Data Engineer Certification Exam 認定 DEA-C01 試験問題 (Q36-Q41):

質問 # 36
A company built a sales reporting system with Python, connecting to Snowflake using the Python Connector.
Based on the user's selections, the system generates the SQL queries needed to fetch the data for the report First it gets the customers that meet the given query parameters (on average 1000 customer records for each report run) and then it loops the customer records sequentially Inside that loop it runs the generated SQL clause for the current customer to get the detailed data for that customer number from the sales data table When the Data Engineer tested the individual SQL clauses they were fast enough (1 second to get the customers 0 5 second to get the sales data for one customer) but the total runtime of the report is too long How can this situation be improved?

A. Increase the number of maximum clusters of the virtual warehouse
B. Define a clustering key for the sales data table
C. Increase the size of the virtual warehouse
D. Rewrite the report to eliminate the use of the loop construct

正解：D

解説：
Explanation
This option is the best way to improve the situation, as using a loop construct to run SQL queries for each customer is very inefficient and slow. Instead, the report should be rewritten to use a single SQL query that joins the customer and sales data tables and applies the query parameters as filters. This way, the report can leverage Snowflake's parallel processing and optimization capabilities and reduce the network overhead and latency.

質問 # 37
A company uses an Amazon QuickSight dashboard to monitor usage of one of the company's applications. The company uses AWS Glue jobs to process data for the dashboard. The company stores the data in a single Amazon S3 bucket. The company adds new data every day.
A data engineer discovers that dashboard queries are becoming slower over time. The data engineer determines that the root cause of the slowing queries is long-running AWS Glue jobs.
Which actions should the data engineer take to improve the performance of the AWS Glue jobs?
(Choose two.)

A. Convert the AWS Glue schema to the DynamicFrame schema class.
B. Partition the data that is in the S3 bucket. Organize the data by year, month, and day.
C. Increase the AWS Glue instance size by scaling up the worker type.
D. Modify the IAM role that grants access to AWS glue to grant access to all S3 features.
E. Adjust AWS Glue job scheduling frequency so the jobs run half as many times each day.

正解：B、C

質問 # 38
A company receives a daily file that contains customer data in .xls format. The company stores the file in Amazon S3. The daily file is approximately 2 GB in size.
A data engineer concatenates the column in the file that contains customer first names and the column that contains customer last names. The data engineer needs to determine the number of distinct customers in the file.
Which solution will meet this requirement with the LEAST operational effort?

A. Create an AWS Glue crawler to create an AWS Glue Data Catalog of the S3 file. Run SQL queries from Amazon Athena to calculate the number of distinct customers.
B. Create and run an Apache Spark job in Amazon EMR Serverless to calculate the number of distinct customers.
C. Use AWS Glue DataBrew to create a recipe that uses the COUNT_DISTINCT aggregate function to calculate the number of distinct customers.
D. Create and run an Apache Spark job in an AWS Glue notebook. Configure the job to read the S3 file and calculate the number of distinct customers.

正解：C

解説：
AWS Glue DataBrew: AWS Glue DataBrew is a visual data preparation tool that allows data engineers and data analysts to clean and normalize data without writing code. Using DataBrew, a data engineer could create a recipe that includes the concatenation of the customer first and last names and then use the COUNT_DISTINCT function. This would not require complex code and could be performed through the DataBrew user interface, representing a lower operational effort.

質問 # 39
A company is building data processing pipelines by using AWS Glue. The pipelines access data stored in Amazon S3. The company has organized the data into folders with prefixes that represent different classification levels. The company needs to restrict AWS Glue jobs to access only specific prefixes based on the data classification. The company must also restrict access to business hours (9 AM to 5 PM). Which elements must the company include in a custom IAM policy to meet these requirements?

A. A Condition element that uses the s3:ResourceAccount condition key to restrict bucket access and a Deny statement that applies outside of business hours
B. A Resource element with S3 object Amazon Resource Name (ARN) patterns that use wildcards for each prefix and a Condition element that uses the $util.time variable with TimeGreaterThan and TimeLessThan operators
C. A Resource element with S3 object Amazon Resource Name (ARN) patterns that use wildcards for each prefix and a Condition element that uses the aws:CurrentTime condition key with DateGreaterThan and DateLessThan operators
D. A Condition element that uses the s3:prefix condition key to restrict folder access and aws:CurrentTime with DateGreaterThanEquals and DateLessThanEquals to restrict hours of operation

正解：C

解説：
IAM policies can restrict access to specific S3 prefixes by defining object ARNs with wildcard patterns in the Resource element. Time-based access control is implemented using the aws:CurrentTime condition key with DateGreaterThan and DateLessThan operators to enforce business-hour access.

質問 # 40
A company stores data in Amazon S3 and Amazon RDS. The company needs to apply technical controls to meet security requirements. The company must generate backups of the data and retain the backups for specified retention periods. The company must protect the backups from accidental or malicious deletion during the retention periods.
Which solution will meet these requirements with the LEAST operational overhead?

A. Create S3 buckets with versioning and Cross-Region Replication enabled. Set a backup retention period and backup window for each RDS DB instance. Use Amazon RDS automated backups.Take additional snapshots as required.
B. Create S3 buckets with versioning and MFA Delete enabled. Set a backup retention period and backup window for each RDS DB instance. Use the automated backup feature of Amazon RDS, and take additional snapshots as required.
C. Create S3 buckets with versioning and Same-Region Replication enabled. Set a backup retention period and backup window for each RDS DB instance. Use the automated backup feature of Amazon RDS. Take additional snapshots as required.
D. Create a backup plan in AWS Backup. Specify the backup schedule, set window and lifecycle values, and select a backup vault. Assign the Amazon S3 and Amazon RDS resources to the backup plan. Create a vault lock in compliance mode.

正解：D

解説：
AWS Backup centrally automates backups for S3 and RDS with scheduled plans and lifecycle policies, and Vault Lock (compliance mode) enforces WORM immutability to prevent modification or deletion during retention, meeting security and retention requirements with minimal administration.

質問 # 41
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DEA-C01資格認定は重要な課題になっていて、この資格認定書を所有している人は会社に得られる給料が高いです。我々DEA-C01問題集を利用し、試験に参加しましょう。試験に成功したら、あなたの知識と能力を証明することができます。あなたはこれらのDEA-C01資格認定を持つ人々の一員になれると、いい仕事を探させます。

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