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A company wants to research user turnover by analyzing the past 3 months of user activities. With millions of users, 1.5 TB of uncompressed data is generated each day. A 30-node Amazon Redshift cluster with 2.56 TB of solid state drive (SSD) storage for each node is required to meet the query performance goals. The company wants to run an additional analysis on a year’s worth of historical data to examine trends indicating which features are most popular. This analysis will be done once a week. What is the MOST cost-effective solution?
A bank is building an Amazon S3 data lake. The bank wants a single data repository for customer data needs, such as personalized recommendations. The bank needs to use Amazon Kinesis Data Firehose to ingest customers' personal information, bank accounts, and transactions in near real time from a transactional relational database. All personally identifiable information (Pll) that is stored in the S3 bucket must be masked. The bank has enabled versioning for the S3 bucket. Which solution will meet these requirements?
A company uses Amazon Redshift as its data warehouse. A new table has columns that contain sensitive data. The data in the table will eventually be referenced by several existing queries that run many times a day. A data analyst needs to load 100 billion rows of data into the new table. Before doing so, the data analyst must ensure that only members of the auditing group can read the columns containing sensitive data. How can the data analyst meet these requirements with the lowest maintenance overhead?
A company is building a data lake and needs to ingest data from a relational database that has time-series data. The company wants to use managed services to accomplish this. The process needs to be scheduled daily and bring incremental data only from the source into Amazon S3. What is the MOST cost-effective approach to meet these requirements?
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 company wants to optimize the cost of its data and analytics platform. The company is ingesting a number of .csv and JSON files in Amazon S3 from various data sources. Incoming data is expected to be 50 GB each day. The company is using Amazon Athena to query the raw data in Amazon S3 directly. Most queries aggregate data from the past 12 months, and data that is older than 5 years is infrequently queried. The typical query scans about 500 MB of data and is expected to return results in less than 1 minute. The raw data must be retained indefinitely for compliance requirements. Which solution meets the company’s requirements?
A company wants to use a data lake that is hosted on Amazon S3 to provide analytics services for historical data. 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 manufacturing company has been collecting IoT sensor data from devices on its factory floor for a year and is storing the data in Amazon Redshift for daily analysis. A data analyst has determined that, at an expected ingestion rate of about 2 TB per day, the cluster will be undersized in less than 4 months. A long-term solution is needed. The data analyst has indicated that most queries only reference the most recent 13 months of data, yet there are also quarterly reports that need to query all the data generated from the past 7 years. The chief technology officer (CTO) is concerned about the costs, administrative effort, and performance of a long-term solution. Which solution should the data analyst use to meet these requirements?
A company uses Amazon Redshift for its data warehouse. The company is running an ET L process that receives data in data parts from five third-party providers. The data parts contain independent records that are related to one specific job. The company receives the data parts at various times throughout each day. A data analytics specialist must implement a solution that loads the data into Amazon Redshift only after the company receives all five data parts. Which solution will meet these requirements?
A company needs to implement a near-real-time messaging system for hotel inventory. The messages are collected from 1,000 data sources and contain hotel inventory data. The data is then processed and distributed to 20 HTTP endpoint destinations. The range of data size for messages is 2-500 KB. The messages must be delivered to each destination in order. The performance of a single destination HTTP endpointshould not impact the performance of the delivery for other destinations. Which solution meets these requirements with the LOWEST latency from message ingestion to delivery?

Question 102 - DAS-C01 discussion

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A company needs to store objects containing log data in JSON format. The objects are generated by eight applications running in AWS. Six of the applications generate a total of 500 KiB of data per second, and two of the applications can generate up to 2 MiB of data per second.

A data engineer wants to implement a scalable solution to capture and store usage data in an Amazon S3 bucket. The usage data objects need to be reformatted, converted to .csv format, and then compressed before they are stored in Amazon S3. The company requires the solution to include the least custom code possible and has authorized the data engineer to request a service quota increase if needed. Which solution meets these requirements?

A.
Configure an Amazon Kinesis Data Firehose delivery stream for each application. Write AWS Lambda functions to read log data objects from the stream for each application. Have the function perform reformatting and .csv conversion.Enable compression on all the delivery streams.
Answers
A.
Configure an Amazon Kinesis Data Firehose delivery stream for each application. Write AWS Lambda functions to read log data objects from the stream for each application. Have the function perform reformatting and .csv conversion.Enable compression on all the delivery streams.
B.
Configure an Amazon Kinesis data stream with one shard per application. Write an AWS Lambda function to read usage data objects from the shards. Have the function perform .csv conversion, reformatting, and compression of thedata. Have the function store the output in Amazon S3.
Answers
B.
Configure an Amazon Kinesis data stream with one shard per application. Write an AWS Lambda function to read usage data objects from the shards. Have the function perform .csv conversion, reformatting, and compression of thedata. Have the function store the output in Amazon S3.
C.
Configure an Amazon Kinesis data stream for each application. Write an AWS Lambda function to read usage data objects from the stream for each application. Have the function perform .csv conversion, reformatting, and compressionof the data. Have the function store the output in Amazon S3.
Answers
C.
Configure an Amazon Kinesis data stream for each application. Write an AWS Lambda function to read usage data objects from the stream for each application. Have the function perform .csv conversion, reformatting, and compressionof the data. Have the function store the output in Amazon S3.
D.
Store usage data objects in an Amazon DynamoDB table. Configure a DynamoDB stream to copy the objects to an S3 bucket. Configure an AWS Lambda function to be triggered when objects are written to the S3 bucket. Have thefunction convert the objects into .csv format.
Answers
D.
Store usage data objects in an Amazon DynamoDB table. Configure a DynamoDB stream to copy the objects to an S3 bucket. Configure an AWS Lambda function to be triggered when objects are written to the S3 bucket. Have thefunction convert the objects into .csv format.
Suggested answer: B
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asked 16/09/2024
Ronald Buffing
40 questions
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