DAS-C01無料問題集「Amazon AWS Certified Data Analytics

質問 1

A company developed a new elections reporting website that uses Amazon Kinesis Data Firehose to deliver full logs from AWS WAF to an Amazon S3 bucket. The company is now seeking a low-cost option to perform this infrequent data analysis with visualizations of logs in a way that requires minimal development effort.
Which solution meets these requirements?

（A）Use an AWS Glue crawler to create and update a table in the Glue data catalog from the logs. Use Athena to perform ad-hoc analyses and use Amazon QuickSight to develop data visualizations.

（B）Create an Amazon EMR cluster and use Amazon S3 as the data source. Create an Apache Spark job to perform ad-hoc analyses and use Amazon QuickSight to develop data visualizations.

（C）Create an AWS Lambda function to convert the logs into .csv format. Then add the function to the Kinesis Data Firehose transformation configuration. Use Amazon Redshift to perform ad-hoc analyses of the logs using SQL queries and use Amazon QuickSight to develop data visualizations.

（D）Create a second Kinesis Data Firehose delivery stream to deliver the log files to Amazon Elasticsearch Service (Amazon ES). Use Amazon ES to perform text-based searches of the logs for ad-hoc analyses and use Kibana for data visualizations.

正解：A 解答を投票する

解説: (JPNTest メンバーにのみ表示されます)

質問 2

A company wants to collect and process events data from different departments in near-real time. Before storing the data in Amazon S3, the company needs to clean the data by standardizing the format of the address and timestamp columns. The data varies in size based on the overall load at each particular point in time. A single data record can be 100 KB-10 MB.
How should a data analytics specialist design the solution for data ingestion?

（A）Use Amazon Simple Queue Service (Amazon SQS). Configure an AWS Lambda function to read events from the SQS queue and upload the events to Amazon S3.

（B）Use Amazon Kinesis Data Streams. Configure a stream for the raw data. Use a Kinesis Agent to write data to the stream. Create an Amazon Kinesis Data Analytics application that reads data from the raw stream, cleanses it, and stores the output to Amazon S3.

（C）Use Amazon Managed Streaming for Apache Kafka. Configure a topic for the raw data. Use a Kafka producer to write data to the topic. Create an application on Amazon EC2 that reads data from the topic by using the Apache Kafka consumer API, cleanses the data, and writes to Amazon S3.

（D）Use Amazon Kinesis Data Firehose. Configure a Firehose delivery stream with a preprocessing AWS Lambda function for data cleansing. Use a Kinesis Agent to write data to the delivery stream. Configure Kinesis Data Firehose to deliver the data to Amazon S3.

正解：D 解答を投票する

質問 3

A company ingests a large set of sensor data in nested JSON format from different sources and stores it in an Amazon S3 bucket. The sensor data must be joined with performance data currently stored in an Amazon Redshift cluster.
A business analyst with basic SQL skills must build dashboards and analyze this data in Amazon QuickSight. A data engineer needs to build a solution to prepare the data for use by the business analyst. The data engineer does not know the structure of the JSON file. The company requires a solution with the least possible implementation effort.
Which combination of steps will create a solution that meets these requirements? (Select THREE.)

（A）Use an AWS Glue crawler to catalog the data.

（B）Use QuickSight to create an Amazon Redshift data source to read the native Amazon Redshift tables.

（C）Use an AWS Glue ETL job with the Regionalize class to un-nest the data and write to Amazon Redshift tables.

（D）Use an AWS Glue ETL job to convert the data into Apache Parquet format and write to Amazon S3.

（E）Use an AWS Glue ETL job with the ApplyMapping class to un-nest the data and write to Amazon Redshift tables.

（F）Use QuickSight to create an Amazon Athena data source to read the Apache Parquet files in Amazon S3.

正解：A、B、C 解答を投票する

質問 4

A company is sending historical datasets to Amazon S3 for storage. A data engineer at the company wants to make these datasets available for analysis using Amazon Athen a. The engineer also wants to encrypt the Athena query results in an S3 results location by using AWS solutions for encryption. The requirements for encrypting the query results are as follows:
Use custom keys for encryption of the primary dataset query results.
Use generic encryption for all other query results.
Provide an audit trail for the primary dataset queries that shows when the keys were used and by whom.
Which solution meets these requirements?

（A）Use server-side encryption with customer-provided encryption keys (SSE-C) for the primary dataset. Use server-side encryption with S3 managed encryption keys (SSE-S3) for the other datasets.

（B）Use client-side encryption with AWS Key Management Service (AWS KMS) customer managed keys for the primary dataset. Use S3 client-side encryption with client-side keys for the other datasets.

（C）Use server-side encryption with S3 managed encryption keys (SSE-S3) for the primary dataset. Use SSE-S3 for the other datasets.

（D）Use server-side encryption with AWS KMS managed customer master keys (SSE-KMS CMKs) for the primary dataset. Use server-side encryption with S3 managed encryption keys (SSE-S3) for the other datasets.

正解：C 解答を投票する

質問 5

A manufacturing company uses Amazon S3 to store its dat
a. The company wants to use AWS Lake Formation to provide granular-level security on those data assets. The data is in Apache Parquet format. The company has set a deadline for a consultant to build a data lake.
How should the consultant create the MOST cost-effective solution that meets these requirements?

（A）To create the data catalog, run an AWS Glue crawler on the existing Parquet data. Register the Amazon S3 path and then apply permissions through Lake Formation to provide granular-level security.

（B）Run Lake Formation blueprints to move the data to Lake Formation. Once Lake Formation has the data, apply permissions on Lake Formation.

（C）Create multiple IAM roles for different users and groups. Assign IAM roles to different data assets in Amazon S3 to create table-based and column-based access controls.

（D）Install Apache Ranger on an Amazon EC2 instance and integrate with Amazon EMR. Using Ranger policies, create role-based access control for the existing data assets in Amazon S3.

正解：B 解答を投票する

解説: (JPNTest メンバーにのみ表示されます)

質問 6

A company stores Apache Parquet-formatted files in Amazon S3 The company uses an AWS Glue Data Catalog to store the table metadata and Amazon Athena to query and analyze the data The tables have a large number of partitions The queries are only run on small subsets of data in the table A data analyst adds new time partitions into the table as new data arrives The data analyst has been asked to reduce the query runtime Which solution will provide the MOST reduction in the query runtime?

（A）Add more partitions to be used over the table. Then filter over two partitions and put all columns in the WHERE clause

（B）Convert the Parquet files to the Apache ORC file format. Then attempt to query the data again

（C）Convert the Parquet files to the csv file format..Then attempt to query the data again

（D）Use partition projection to speed up the processing of the partitioned table

正解：D 解答を投票する

質問 7

A company wants to use automatic machine learning (ML) to create and visualize forecasts of complex scenarios and trends.
Which solution will meet these requirements with the LEAST management overhead?

（A）Use Amazon QuickSight to visualize the data. Use ML-powered forecasting in QuickSight to create forecasts.

（B）Use Amazon SageMaker inference pipelines to create and update forecasts. Use Amazon QuickSight to visualize the combined data.

（C）Use a prebuilt ML AMI from the AWS Marketplace to create forecasts. Use Amazon QuickSight to visualize the data.

（D）Use an AWS Glue ML job to transform the data and create forecasts. Use Amazon QuickSight to visualize the data.

正解：A 解答を投票する

質問 8

A market data company aggregates external data sources to create a detailed view of product consumption in different countries. The company wants to sell this data to external parties through a subscription. To achieve this goal, the company needs to make its data securely available to external parties who are also AWS users.
What should the company do to meet these requirements with the LEAST operational overhead?

（A）Store the data in Amazon S3. Share the data by using S3 bucket ACLs.

（B）Upload the data to AWS Data Exchange for storage. Share the data by using the AWS Data Exchange sharing wizard.

（C）Store the data in Amazon S3. Share the data by using presigned URLs for security.

（D）Upload the data to AWS Data Exchange for storage. Share the data by using presigned URLs for security.

正解：C 解答を投票する

質問 9

A company wants to use a data lake that is hosted on Amazon S3 to provide analytics services for historical dat a. The data lake consists of 800 tables but is expected to grow to thousands of tables. More than 50 departments use the tables, and each department has hundreds of users. Different departments need access to specific tables and columns.
Which solution will meet these requirements with the LEAST operational overhead?

（A）Create an 1AM role for each department. Use AWS Lake Formation based access control to grant each 1AM role access to specific tables and columns. Use Amazon Athena to analyze the data.

（B）Create an 1AM role for each department. Use AWS Lake Formation tag-based access control to grant each 1AM role access to only the relevant resources. Create LF-tags that are attached to tables and columns. Use Amazon Athena to analyze the data.

（C）Create an Amazon Redshift cluster for each department. Use AWS Glue to ingest into the Redshift cluster only the tables and columns that are relevant to that department. Create Redshift database users. Grant the users access to the relevant department's Redshift cluster. Use Amazon Redshift to analyze the data.

（D）Create an Amazon EMR cluster for each department. Configure an 1AM service role for each EMR cluster to access

（E）relevant S3 files. For each department's users, create an 1AM role that provides access to the relevant EMR cluster. Use Amazon EMR to analyze the data.

正解：B 解答を投票する

質問 10

A company analyzes historical data and needs to query data that is stored in Amazon S3. New data is generated daily as .csv files that are stored in Amazon S3. The company's analysts are using Amazon Athena to perform SQL queries against a recent subset of the overall dat a. The amount of data that is ingested into Amazon S3 has increased substantially over time, and the query latency also has increased.
Which solutions could the company implement to improve query performance? (Choose two.)

（A）Run a daily AWS Glue ETL job to compress the data files by using the .gzip format. Query the compressed data.

（B）Use Athena to extract the data and store it in Apache Parquet format on a daily basis. Query the extracted data.

（C）Run a daily AWS Glue ETL job to compress the data files by using the .lzo format. Query the compressed data.

（D）Run a daily AWS Glue ETL job to convert the data files to Apache Parquet and to partition the converted files. Create a periodic AWS Glue crawler to automatically crawl the partitioned data on a daily basis.

（E）Use MySQL Workbench on an Amazon EC2 instance, and connect to Athena by using a JDBC or ODBC connector. Run the query from MySQL Workbench instead of Athena directly.

正解：B、D 解答を投票する

解説: (JPNTest メンバーにのみ表示されます)

質問 11

An online retail company with millions of users around the globe wants to improve its ecommerce analytics capabilities. Currently, clickstream data is uploaded directly to Amazon S3 as compressed files. Several times each day, an application running on Amazon EC2 processes the data and makes search options and reports available for visualization by editors and marketers. The company wants to make website clicks and aggregated data available to editors and marketers in minutes to enable them to connect with users more effectively.
Which options will help meet these requirements in the MOST efficient way? (Choose two.)

（A）Use Amazon Kinesis Data Firehose to upload compressed and batched clickstream records to Amazon Elasticsearch Service.

（B）Use Kibana to aggregate, filter, and visualize the data stored in Amazon Elasticsearch Service. Refresh content performance dashboards in near-real time.

（C）Use Amazon Elasticsearch Service deployed on Amazon EC2 to aggregate, filter, and process the data. Refresh content performance dashboards in near-real time.

（D）Upload clickstream records from Amazon S3 to Amazon Kinesis Data Streams and use a Kinesis Data Streams consumer to send records to Amazon Elasticsearch Service.

（E）Upload clickstream records to Amazon S3 as compressed files. Then use AWS Lambda to send data to Amazon Elasticsearch Service from Amazon S3.

正解：A、B 解答を投票する

質問 12

An Amazon Redshift database contains sensitive user dat
a. Logging is necessary to meet compliance requirements. The logs must contain database authentication attempts, connections, and disconnections. The logs must also contain each query run against the database and record which database user ran each query.
Which steps will create the required logs?

（A）Enable audit logging for Amazon Redshift using the AWS Management Console or the AWS CLI.

（B）Allow access to the Amazon Redshift database using AWS IAM only. Log access using AWS CloudTrail.

（C）Enable and download audit reports from AWS Artifact.

（D）Enable Amazon Redshift Enhanced VPC Routing. Enable VPC Flow Logs to monitor traffic.

正解：A 解答を投票する

質問 13

A technology company is creating a dashboard that will visualize and analyze time-sensitive dat a. The data will come in through Amazon Kinesis Data Firehose with the butter interval set to 60 seconds. The dashboard must support near-real-time data.
Which visualization solution will meet these requirements?

（A）Select Amazon S3 as the endpoint for Kinesis Data Firehose. Use AWS Glue to catalog the data and Amazon Athena to query it. Connect Amazon QuickSight with SPICE to Athena to create the desired analyses and visualizations.

（B）Select Amazon Redshift as the endpoint for Kinesis Data Firehose. Connect Amazon QuickSight with SPICE to Amazon Redshift to create the desired analyses and visualizations.

（C）Select Amazon S3 as the endpoint for Kinesis Data Firehose. Read data into an Amazon SageMaker Jupyter notebook and carry out the desired analyses and visualizations.

（D）Select Amazon Elasticsearch Service (Amazon ES) as the endpoint for Kinesis Data Firehose. Set up a Kibana dashboard using the data in Amazon ES with the desired analyses and visualizations.

正解：D 解答を投票する

質問 14

A data engineer is using AWS Glue ETL jobs to process data at frequent intervals The processed data is then copied into Amazon S3 The ETL jobs run every 15 minutes. The AWS Glue Data Catalog partitions need to be updated automatically after the completion of each job Which solution will meet these requirements MOST cost-effectively?

（A）Use the AWS Glue Data Catalog to manage the data catalog Update the AWS Glue ETL code to include the enableUpdateCatalog and partitionKeys arguments.

（B）Use the AWS Glue Data Catalog to manage the data catalog Define an AWS Glue workflow for the ETL process Define a trigger within the workflow that can start the crawler when an ETL job run is complete

（C）Use an Apache Hive metastore to manage the data catalog Update the AWS Glue ETL code to include the enableUpdateCatalog and partitionKeys arguments.

（D）Use the AWS Glue Data Catalog to manage the data catalog Use AWS Glue Studio to manage ETL jobs. Use the AWS Glue Studio feature that supports updates to the AWS Glue Data Catalog during job runs.

正解：B 解答を投票する

質問 15

A team of data scientists plans to analyze market trend data for their company's new investment strategy. The trend data comes from five different data sources in large volumes. The team wants to utilize Amazon Kinesis to support their use case. The team uses SQL-like queries to analyze trends and wants to send notifications based on certain significant patterns in the trends. Additionally, the data scientists want to save the data to Amazon S3 for archival and historical re-processing, and use AWS managed services wherever possible. The team wants to implement the lowest-cost solution.
Which solution meets these requirements?

（A）Publish data to one Kinesis data stream. Deploy a custom application using the Kinesis Client Library (KCL) for analyzing trends, and send notifications using Amazon SNS. Configure Kinesis Data Firehose on the Kinesis data stream to persist data to an S3 bucket.

（B）Publish data to two Kinesis data streams. Deploy Kinesis Data Analytics to the first stream for analyzing trends, and configure an AWS Lambda function as an output to send notifications using Amazon SNS. Configure Kinesis Data Firehose on the second Kinesis data stream to persist data to an S3 bucket.

（C）Publish data to two Kinesis data streams. Deploy a custom application using the Kinesis Client Library (KCL) to the first stream for analyzing trends, and send notifications using Amazon SNS. Configure Kinesis Data Firehose on the second Kinesis data stream to persist data to an S3 bucket.

（D）Publish data to one Kinesis data stream. Deploy Kinesis Data Analytic to the stream for analyzing trends, and configure an AWS Lambda function as an output to send notifications using Amazon SNS. Configure Kinesis Data Firehose on the Kinesis data stream to persist data to an S3 bucket.

正解：D 解答を投票する

DAS-C01 無料問題集「Amazon AWS Certified Data Analytics - Specialty (DAS-C01)」

弊社を連絡する

関連リンク

トップ試験