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DAS-C01 - AWS Certified Data Analytics - Specialty

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DAS-C01 Questions and Answers

Question # 1

A company receives data from its vendor in JSON format with a timestamp in the file name. The vendor uploads the data to an Amazon S3 bucket, and the data is registered into the company’s data lake for analysis and reporting. The company has configured an S3 Lifecycle policy to archive all files to S3 Glacier after 5 days.

The company wants to ensure that its AWS Glue crawler catalogs data only from S3 Standard storage and ignores the archived files. A data analytics specialist must implement a solution to achieve this goal without changing the current S3 bucket configuration.

Which solution meets these requirements?


Use the exclude patterns feature of AWS Glue to identify the S3 Glacier files for the crawler to exclude.


Schedule an automation job that uses AWS Lambda to move files from the original S3 bucket to a new S3 bucket for S3 Glacier storage.


Use the excludeStorageClasses property in the AWS Glue Data Catalog table to exclude files on S3 Glacier storage


Use the include patterns feature of AWS Glue to identify the S3 Standard files for the crawler to include.

Question # 2

A transport company wants to track vehicular movements by capturing geolocation records. The records are 10 B in size and up to 10,000 records are captured each second. Data transmission delays of a few minutes are acceptable, considering unreliable network conditions. The transport company decided to use Amazon Kinesis Data Streams to ingest the data. The company is looking for a reliable mechanism to send data to Kinesis Data Streams while maximizing the throughput efficiency of the Kinesis shards.

Which solution will meet the company’s requirements?


Kinesis Agent


Kinesis Producer Library (KPL)


Kinesis Data Firehose


Kinesis SDK

Question # 3

A banking company wants to collect large volumes of transactional data using Amazon Kinesis Data Streams for real-time analytics. The company uses PutRecord to send data to Amazon Kinesis, and has observed network outages during certain times of the day. The company wants to obtain exactly once semantics for the entire processing pipeline.

What should the company do to obtain these characteristics?


Design the application so it can remove duplicates during processing be embedding a unique ID in each record.


Rely on the processing semantics of Amazon Kinesis Data Analytics to avoid duplicate processing of events.


Design the data producer so events are not ingested into Kinesis Data Streams multiple times.


Rely on the exactly one processing semantics of Apache Flink and Apache Spark Streaming included in Amazon EMR.

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