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Question 96

A company is building an analytical solution that includes Amazon S3 as data lake storage and Amazon Redshift for data warehousing. The company wants to use Amazon Redshift Spectrum to query the data that is stored in Amazon S3.
Which steps should the company take to improve performance when the company uses Amazon Redshift Spectrum to query the S3 data files? (Select THREE ) Use gzip compression with individual file sizes of 1-5 GB

A.Use a columnar storage file format
B.Keep all files about the same size.
C.Partition the data based on the most common query predicates
D.Use file formats that are not splittable
E.Split the data into KB-sized files.

Question 97

A company wants to improve the data load time of a sales data dashboard. Data has been collected as .csv files and stored within an Amazon S3 bucket that is partitioned by date. The data is then loaded to an Amazon Redshift data warehouse for frequent analysis. The data volume is up to 500 GB per day.
Which solution will improve the data loading performance?

A.Compress .csv files and use an INSERT statement to ingest data into Amazon Redshift.
B.Split large .csv files, then use a COPY command to load data into Amazon Redshift.
C.Use Amazon Kinesis Data Firehose to ingest data into Amazon Redshift.
D.Load the .csv files in an unsorted key order and vacuum the table in Amazon Redshift.

Question 98

Once a month, a company receives a 100 MB .csv file compressed with gzip. The file contains 50,000 property listing records and is stored in Amazon S3 Glacier. The company needs its data analyst to query a subset of the data for a specific vendor.
What is the most cost-effective solution?

A.Load the data to Amazon S3 and query it with Amazon Athena.
B.Load the data to Amazon S3 and query it with Amazon Redshift Spectrum.
C.Query the data from Amazon S3 Glacier directly with Amazon Glacier Select.
D.Load the data into Amazon S3 and query it with Amazon S3 Select.

Question 99

A company uses Amazon kinesis Data Streams to ingest and process customer behavior information from application users each day. A data analytics specialist notices that its data stream is throttling. The specialist has turned on enhanced monitoring for the Kinesis data stream and has verified that the data stream did not exceed the data limits. The specialist discovers that there are hot shards Which solution will resolve this issue?

A.Increase the number of shards Split the size of the log records.
B.Use a random partition key to ingest the records.
C.Limit the number of records that are sent each second by the producer to match the capacity of the stream.
D.Decrease the size of the records that are sent from the producer to match the capacity of the stream.

Question 100

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 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.
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 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.