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NEW QUESTION 33 A company is planning to do a proof of concept for a machine earning (ML) project using Amazon SageMaker with a subset of existing on-premises data hosted in the company's 3 TB data warehouse. For part of the project, AWS Direct Connect is established and tested. To prepare the data for ML, data analysts are performing data curation. The data analysts want to perform multiple step, including mapping, dropping null fields, resolving choice, and splitting fields. The company needs the fastest solution to curate the data for this project. Which solution meets these requirements?

• A. Ingest data into Amazon S3 using AWS DataSync and use Apache Spark scrips to curate the data in an Amazon EMR cluster. Store the curated data in Amazon S3 for ML processing.
• B. Take a full backup of the data store and ship the backup files using AWS Snowball. Upload Snowball data into Amazon S3 and schedule data curation jobs using AWS Batch to prepare the data for ML.
• C. Ingest data into Amazon S3 using AWS DMS. Use AWS Glue to perform data curation and store the data in Amazon 3 for ML processing.
• D. Create custom ETL jobs on-premises to curate the data. Use AWS DMS to ingest data into Amazon S3 for ML processing.

Answer: C   NEW QUESTION 34 A company is migrating from an on-premises Apache Hadoop cluster to an Amazon EMR cluster. The cluster runs only during business hours. Due to a company requirement to avoid intraday cluster failures, the EMR cluster must be highly available. When the cluster is terminated at the end of each business day, the data must persist. Which configurations would enable the EMR cluster to meet these requirements? (Choose three.)

• A. AWS Glue Data Catalog as the metastore for Apache Hive
• B. Multiple master nodes in multiple Availability Zones
• C. Hadoop Distributed File System (HDFS) for storage
• D. Multiple master nodes in a single Availability Zone
• E. EMR File System (EMRFS) for storage
• F. MySQL database on the master node as the metastore for Apache Hive

Answer: A,D,E Explanation: Explanation https://docs.aws.amazon.com/emr/latest/ManagementGuide/emr-plan-ha.html "Note : The cluster can reside only in one Availability Zone or subnet."   NEW QUESTION 35 A company is reading data from various customer databases that run on Amazon RDS. The databases contain many inconsistent fields For example, a customer record field that is placeid in one database is locationid in another database. The company wants to link customer records across different databases, even when many customer record fields do not match exactly Which solution will meet these requirements with the LEAST operational overhead?

• A. Create an AWS Glue crawler to crawl the data in the databases Use Amazon SageMaker to construct Apache Spark ML pipelines to find duplicate records in the data
• B. Create an Amazon EMR cluster to process and analyze data in the databases. Connect to the Apache Zeppelin notebook, and use Apache Spark ML to find duplicate records in the data. Evaluate and tune the model by evaluating performance and results of finding duplicates
• C. Create an AWS Glue crawler to crawl the databases. Use the FindMatches transform to find duplicate records in the data Evaluate and tune the transform by evaluating performance and results of finding matches
• D. Create an Amazon EMR cluster to process and analyze data in the databases Connect to the Apache Zeppelin notebook, and use the FindMatches transform to find duplicate records in the data.

Answer: C   NEW QUESTION 36 A reseller that has thousands of AWS accounts receives AWS Cost and Usage Reports in an Amazon S3 bucket The reports are delivered to the S3 bucket in the following format <examp/e-reporT-prefix>/<examp/e-report-rtame>/yyyymmdd-yyyymmdd/<examp/e-report-name> parquet An AWS Glue crawler crawls the S3 bucket and populates an AWS Glue Data Catalog with a table Business analysts use Amazon Athena to query the table and create monthly summary reports for the AWS accounts The business analysts are experiencing slow queries because of the accumulation of reports from the last 5 years The business analysts want the operations team to make changes to improve query performance Which action should the operations team take to meet these requirements?

• A. Change the file format to csv.zip.
• B. Partition the data by month and account ID
• C. Partition the data by date and account ID
• D. Partition the data by account ID, year, and month

Answer: C   NEW QUESTION 37 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 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.
• B. 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.
• 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 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.

Answer: B   NEW QUESTION 38 ...... 2023 Latest Exam-Killer DAS-C01 PDF Dumps and DAS-C01 Exam Engine Free Share: https://drive.google.com/open?id=1sdCuw844UAXghtfXGnj2OEQy58B1iS8O