A company has a data lake on AWS that ingests sources of data from multiple business units and uses Amazon Athena for queries. The storage layer is Amazon S3 using the AWS Glue Data Catalog. The company wants to make the data available to its data scientists and business analysts. However, the company first needs to manage data access for Athena based on user roles and responsibilities.
What should the company do to apply these access controls with the LEAST operational overhead?

1. A. Define security policy-based rules for the users and applications by role in AWS Lake Formation.
2. B. Define security policy-based rules for the users and applications by role in AWS Identity and Access Management (IAM).
3. C. Define security policy-based rules for the tables and columns by role in AWS Glue.
4. D. Define security policy-based rules for the tables and columns by role in AWS Identity and Access Management (IAM).

Correct Answer: D

An ecommerce company stores customer purchase data in Amazon RDS. The company wants a solution to store and analyze historical data. The most recent 6 months of data will be queried frequently for analytics workloads. This data is several terabytes large. Once a month, historical data for the last 5 years must be accessible and will be joined with the more recent data. The company wants to optimize performance and cost.
Which storage solution will meet these requirements?

1. A. Create a read replica of the RDS database to store the most recent 6 months of dat
2. B. Copy the historical data into Amazon S3. Create an AWS Glue Data Catalog of the data in Amazon S3 and Amazon RD
3. C. Run historical queries using Amazon Athena.
4. D. Use an ETL tool to incrementally load the most recent 6 months of data into an Amazon Redshift cluste
5. E. Run more frequent queries against this cluste
6. F. Create a read replica of the RDS database to run queries on the historical data.
7. G. Incrementally copy data from Amazon RDS to Amazon S3. Create an AWS Glue Data Catalog of the data in Amazon S3. Use Amazon Athena to query the data.
8. H. Incrementally copy data from Amazon RDS to Amazon S3. Load and store the most recent 6 months of data in Amazon Redshif
9. I. Configure an Amazon Redshift Spectrum table to connect to all historical data.

Correct Answer: D

A company has 1 million scanned documents stored as image files in Amazon S3. The documents contain typewritten application forms with information including the applicant first name, applicant last name, application date, application type, and application text. The company has developed a machine learning algorithm to extract the metadata values from the scanned documents. The company wants to allow internal data analysts to analyze and find applications using the applicant name, application date, or application text. The original images should also be downloadable. Cost control is secondary to query performance.
Which solution organizes the images and metadata to drive insights while meeting the requirements?

1. A. For each image, use object tags to add the metadat
2. B. Use Amazon S3 Select to retrieve the files based on the applicant name and application date.
3. C. Index the metadata and the Amazon S3 location of the image file in Amazon Elasticsearch Service.Allow the data analysts to use Kibana to submit queries to the Elasticsearch cluster.
4. D. Store the metadata and the Amazon S3 location of the image file in an Amazon Redshift tabl
5. E. Allow the data analysts to run ad-hoc queries on the table.
6. F. Store the metadata and the Amazon S3 location of the image files in an Apache Parquet file in Amazon S3, and define a table in the AWS Glue Data Catalo
7. G. Allow data analysts to use Amazon Athena to submit custom queries.

Correct Answer: B
https://aws.amazon.com/blogs/machine-learning/automatically-extract-text-and-structured-data-from-documents

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?

1. A. Use an AWS Glue crawler to create and update a table in the Glue data catalog from the log
2. B. Use Athena to perform ad-hoc analyses and use Amazon QuickSight to develop data visualizations.
3. C. 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.
4. D. Create an AWS Lambda function to convert the logs into .csv forma
5. E. Then add the function to the Kinesis Data Firehose transformation configuratio
6. F. Use Amazon Redshift to perform ad-hoc analyses of the logs using SQL queries and use Amazon QuickSight to develop data visualizations.
7. G. Create an Amazon EMR cluster and use Amazon S3 as the data sourc
8. H. Create an Apache Spark job to perform ad-hoc analyses and use Amazon QuickSight to develop data visualizations.

Correct Answer: A
https://aws.amazon.com/blogs/big-data/analyzing-aws-waf-logs-with-amazon-es-amazon-athena-and-amazon-qu

An insurance company has raw data in JSON format that is sent without a predefined schedule through an Amazon Kinesis Data Firehose delivery stream to an Amazon S3 bucket. An AWS Glue crawler is scheduled to run every 8 hours to update the schema in the data catalog of the tables stored in the S3 bucket. Data analysts analyze the data using Apache Spark SQL on Amazon EMR set up with AWS Glue Data Catalog as the metastore. Data analysts say that, occasionally, the data they receive is stale. A data engineer needs to provide access to the most up-to-date data.
Which solution meets these requirements?

1. A. Create an external schema based on the AWS Glue Data Catalog on the existing Amazon Redshift cluster to query new data in Amazon S3 with Amazon Redshift Spectrum.
2. B. Use Amazon CloudWatch Events with the rate (1 hour) expression to execute the AWS Glue crawler every hour.
3. C. Using the AWS CLI, modify the execution schedule of the AWS Glue crawler from 8 hours to 1 minute.
4. D. Run the AWS Glue crawler from an AWS Lambda function triggered by an S3:ObjectCreated:* eventnotification on the S3 bucket.

Correct Answer: D
https://docs.aws.amazon.com/AmazonS3/latest/dev/NotificationHowTo.html "you can use a wildcard (for example, s3:ObjectCreated:*) to request notification when an object is created regardless of the API used" "AWS Lambda can run custom code in response to Amazon S3 bucket events. You upload your custom code to AWS Lambda and create what is called a Lambda function. When Amazon S3 detects an event of a specific type (for example, an object created event), it can publish the event to AWS Lambda and invoke your function in Lambda. In response, AWS Lambda runs your function."