Down To Date DAS-C01 Exam Price For AWS Certified Data Analytics - Specialty Certification

NEW 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?

• A. Use the exclude patterns feature of AWS Glue to identify the S3 Glacier files for the crawler to exclude.
• B. 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.
• C. Use the excludeStorageClasses property in the AWS Glue Data Catalog table to exclude files on S3 Glacier storage
• D. Use the include patterns feature of AWS Glue to identify the S3 Standard files for the crawler to include.

Answer: A

NEW QUESTION 2
A media content company has a streaming playback application. The company wants to collect and analyze the data to provide near-real-time feedback on playback issues. The company needs to consume this data and return results within 30 seconds according to the service-level agreement (SLA). The company needs the consumer to identify playback issues, such as quality during a specified timeframe. The data will be emitted as JSON and may change schemas over time.
Which solution will allow the company to collect data for processing while meeting these requirements?

• A. Send the data to Amazon Kinesis Data Firehose with delivery to Amazon S3. Configure an S3 event trigger an AWS Lambda function to process the dat
• B. The Lambda function will consume the data and process it to identify potential playback issue
• C. Persist the raw data to Amazon S3.
• D. Send the data to Amazon Managed Streaming for Kafka and configure an Amazon Kinesis Analytics for Java application as the consume
• E. The application will consume the data and process it to identify potential playback issue
• F. Persist the raw data to Amazon DynamoDB.
• G. Send the data to Amazon Kinesis Data Firehose with delivery to Amazon S3. Configure Amazon S3 to trigger an event for AWS Lambda to proces
• H. The Lambda function will consume the data and process it to identify potential playback issue
• I. Persist the raw data to Amazon DynamoDB.
• J. Send the data to Amazon Kinesis Data Streams and configure an Amazon Kinesis Analytics for Java application as the consume
• K. The application will consume the data and process it to identify potential playback issue
• L. Persist the raw data to Amazon S3.

Answer: D

Explanation:
https://aws.amazon.com/blogs/aws/new-amazon-kinesis-data-analytics-for-java/

NEW QUESTION 3
A financial company uses Apache Hive on Amazon EMR for ad-hoc queries. Users are complaining of sluggish performance.
A data analyst notes the following:
Approximately 90% of queries are submitted 1 hour after the market opens.
Hadoop Distributed File System (HDFS) utilization never exceeds 10%.
Which solution would help address the performance issues?

• A. Create instance fleet configurations for core and task node
• B. Create an automatic scaling policy to scale out the instance groups based on the Amazon CloudWatch CapacityRemainingGB metri
• C. Create an automatic scaling policy to scale in the instance fleet based on the CloudWatch CapacityRemainingGB metric.
• D. Create instance fleet configurations for core and task node
• E. Create an automatic scaling policy to scale out the instance groups based on the Amazon CloudWatch YARNMemoryAvailablePercentage metri
• F. Create an automatic scaling policy to scale in the instance fleet based on the CloudWatch YARNMemoryAvailablePercentage metric.
• G. Create instance group configurations for core and task node
• H. Create an automatic scaling policy to scale out the instance groups based on the Amazon CloudWatch CapacityRemainingGB metri
• I. Create anautomatic scaling policy to scale in the instance groups based on the CloudWatch CapacityRemainingGB metric.
• J. Create instance group configurations for core and task node
• K. Create an automatic scaling policy to scale out the instance groups based on the Amazon CloudWatch YARNMemoryAvailablePercentage metri
• L. Create an automatic scaling policy to scale in the instance groups based on the CloudWatch YARNMemoryAvailablePercentage metric.

Answer: D

Explanation:
https://docs.aws.amazon.com/emr/latest/ManagementGuide/emr-plan-instances-guidelines.html

NEW QUESTION 4
A large company has a central data lake to run analytics across different departments. Each department uses a separate AWS account and stores its data in an Amazon S3 bucket in that account. Each AWS account uses the AWS Glue Data Catalog as its data catalog. There are different data lake access requirements based on roles. Associate analysts should only have read access to their departmental data. Senior data analysts can have access in multiple departments including theirs, but for a subset of columns only.
Which solution achieves these required access patterns to minimize costs and administrative tasks?

• A. Consolidate all AWS accounts into one accoun
• B. Create different S3 buckets for each department and move all the data from every account to the central data lake accoun
• C. Migrate the individual data catalogs into a central data catalog and apply fine-grained permissions to give to each user the required access to tables and databases in AWS Glue and Amazon S3.
• D. Keep the account structure and the individual AWS Glue catalogs on each accoun
• E. Add a central data lake account and use AWS Glue to catalog data from various account
• F. Configure cross-account access for AWS Glue crawlers to scan the data in each departmental S3 bucket to identify the schema and populate the catalo
• G. Add the senior data analysts into the central account and apply highly detailed access controls in the Data Catalog and Amazon S3.
• H. Set up an individual AWS account for the central data lak
• I. Use AWS Lake Formation to catalog the cross- account location
• J. On each individual S3 bucket, modify the bucket policy to grant S3 permissions to the Lake Formation service-linked rol
• K. Use Lake Formation permissions to addfine-grained access controls to allow senior analysts to view specific tables and columns.
• L. Set up an individual AWS account for the central data lake and configure a central S3 bucke
• M. Use an AWS Lake Formation blueprint to move the data from the various buckets into the central S3 bucke
• N. On each individual bucket, modify the bucket policy to grant S3 permissions to the Lake Formation service-linked rol
• O. Use Lake Formation permissions to add fine-grained access controls for both associate and senior analysts to view specific tables and columns.

Answer: C

Explanation:
Lake Formation provides secure and granular access to data through a new grant/revoke permissions model that augments AWS Identity and Access Management (IAM) policies. Analysts and data scientists can use the full portfolio of AWS analytics and machine learning services, such as Amazon Athena, to access the data. The configured Lake Formation security policies help ensure that users can access only the data that they are authorized to access. Source : https://docs.aws.amazon.com/lake-formation/latest/dg/how-it-works.html

NEW QUESTION 5
A company is building a service to monitor fleets of vehicles. The company collects IoT data from a device in each vehicle and loads the data into Amazon Redshift in near-real time. Fleet owners upload .csv files containing vehicle reference data into Amazon S3 at different times throughout the day. A nightly process loads the vehicle reference data from Amazon S3 into Amazon Redshift. The company joins the IoT data from the device and the vehicle reference data to power reporting and dashboards. Fleet owners are frustrated by waiting a day for the dashboards to update.
Which solution would provide the SHORTEST delay between uploading reference data to Amazon S3 and the change showing up in the owners’ dashboards?

• A. Use S3 event notifications to trigger an AWS Lambda function to copy the vehicle reference data into Amazon Redshift immediately when the reference data is uploaded to Amazon S3.
• B. Create and schedule an AWS Glue Spark job to run every 5 minute
• C. The job inserts reference data into Amazon Redshift.
• D. Send reference data to Amazon Kinesis Data Stream
• E. Configure the Kinesis data stream to directly load the reference data into Amazon Redshift in real time.
• F. Send the reference data to an Amazon Kinesis Data Firehose delivery strea
• G. Configure Kinesis with a buffer interval of 60 seconds and to directly load the data into Amazon Redshift.

Answer: A

NEW QUESTION 6
A company uses the Amazon Kinesis SDK to write data to Kinesis Data Streams. Compliance requirements state that the data must be encrypted at rest using a key that can be rotated. The company wants to meet this encryption requirement with minimal coding effort.
How can these requirements be met?

• A. Create a customer master key (CMK) in AWS KM
• B. Assign the CMK an alia
• C. Use the AWS Encryption SDK, providing it with the key alias to encrypt and decrypt the data.
• D. Create a customer master key (CMK) in AWS KM
• E. Assign the CMK an alia
• F. Enable server-side encryption on the Kinesis data stream using the CMK alias as the KMS master key.
• G. Create a customer master key (CMK) in AWS KM
• H. Create an AWS Lambda function to encrypt and decrypt the dat
• I. Set the KMS key ID in the function’s environment variables.
• J. Enable server-side encryption on the Kinesis data stream using the default KMS key for Kinesis Data Streams.

Answer: B

NEW QUESTION 7
A real estate company has a mission-critical application using Apache HBase in Amazon EMR. Amazon EMR is configured with a single master node. The company has over 5 TB of data stored on an Hadoop Distributed File System (HDFS). The company wants a cost-effective solution to make its HBase data highly available.
Which architectural pattern meets company’s requirements?

• A. Use Spot Instances for core and task nodes and a Reserved Instance for the EMR master node.Configurethe EMR cluster with multiple master node
• B. Schedule automated snapshots using AmazonEventBridge.
• C. Store the data on an EMR File System (EMRFS) instead of HDF
• D. Enable EMRFS consistent view.Create an EMR HBase cluster with multiple master node
• E. Point the HBase root directory to an Amazon S3 bucket.
• F. Store the data on an EMR File System (EMRFS) instead of HDFS and enable EMRFS consistent view.Run two separate EMR clusters in two different Availability Zone
• G. Point both clusters to the same HBase root directory in the same Amazon S3 bucket.
• H. Store the data on an EMR File System (EMRFS) instead of HDFS and enable EMRFS consistent view.Create a primary EMR HBase cluster with multiple master node
• I. Create a secondary EMR HBase read- replica cluster in a separate Availability Zon
• J. Point both clusters to the same HBase root directory in the same Amazon S3 bucket.

Answer: D

NEW QUESTION 8
A company analyzes its data in an Amazon Redshift data warehouse, which currently has a cluster of three dense storage nodes. Due to a recent business acquisition, the company needs to load an additional 4 TB of user data into Amazon Redshift. The engineering team will combine all the user data and apply complex calculations that require I/O intensive resources. The company needs to adjust the cluster's capacity to support the change in analytical and storage requirements.
Which solution meets these requirements?

• A. Resize the cluster using elastic resize with dense compute nodes.
• B. Resize the cluster using classic resize with dense compute nodes.
• C. Resize the cluster using elastic resize with dense storage nodes.
• D. Resize the cluster using classic resize with dense storage nodes.

Answer: C

NEW QUESTION 9
A company currently uses Amazon Athena to query its global datasets. The regional data is stored in Amazon S3 in the us-east-1 and us-west-2 Regions. The data is not encrypted. To simplify the query process and manage it centrally, the company wants to use Athena in us-west-2 to query data from Amazon S3 in both Regions. The solution should be as low-cost as possible.
What should the company do to achieve this goal?

• A. Use AWS DMS to migrate the AWS Glue Data Catalog from us-east-1 to us-west-2. Run Athena queries in us-west-2.
• B. Run the AWS Glue crawler in us-west-2 to catalog datasets in all Region
• C. Once the data is crawled, run Athena queries in us-west-2.
• D. Enable cross-Region replication for the S3 buckets in us-east-1 to replicate data in us-west-2. Once the data is replicated in us-west-2, run the AWS Glue crawler there to update the AWS Glue Data Catalog in us-west-2 and run Athena queries.
• E. Update AWS Glue resource policies to provide us-east-1 AWS Glue Data Catalog access to us-west-2.Once the catalog in us-west-2 has access to the catalog in us-east-1, run Athena queries in us-west-2.

Answer: B

NEW QUESTION 10
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?

• 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.
• B. Use Amazon CloudWatch Events with the rate (1 hour) expression to execute the AWS Glue crawler every hour.
• C. Using the AWS CLI, modify the execution schedule of the AWS Glue crawler from 8 hours to 1 minute.
• D. Run the AWS Glue crawler from an AWS Lambda function triggered by an S3:ObjectCreated:* event notification on the S3 bucket.

Answer: D

Explanation:
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."

NEW QUESTION 11
Three teams of data analysts use Apache Hive on an Amazon EMR cluster with the EMR File System (EMRFS) to query data stored within each teams Amazon S3 bucket. The EMR cluster has Kerberos enabled and is configured to authenticate users from the corporate Active Directory. The data is highly sensitive, so access must be limited to the members of each team.
Which steps will satisfy the security requirements?

• A. For the EMR cluster Amazon EC2 instances, create a service role that grants no access to Amazon S3.Create three additional IAM roles, each granting access to each team’s specific bucke
• B. Add the additional IAM roles to the cluster’s EMR role for the EC2 trust polic
• C. Create a security configuration mapping for the additional IAM roles to Active Directory user groups for each team.
• D. For the EMR cluster Amazon EC2 instances, create a service role that grants no access to Amazon S3.Create three additional IAM roles, each granting access to each team's specific bucke
• E. Add the service role for the EMR cluster EC2 instances to the trust policies for the additional IAM role
• F. Create a security configuration mapping for the additional IAM roles to Active Directory user groups for each team.
• G. For the EMR cluster Amazon EC2 instances, create a service role that grants full access to Amazon S3.Create three additional IAM roles, each granting access to each team’s specific bucke
• H. Add the service role for the EMR cluster EC2 instances to the trust polices for the additional IAM role
• I. Create a security configuration mapping for the additional IAM roles to Active Directory user groups for each team.
• J. For the EMR cluster Amazon EC2 instances, create a service role that grants full access to Amazon S3.Create three additional IAM roles, each granting access to each team's specific bucke
• K. Add the service role for the EMR cluster EC2 instances to the trust polices for the base IAM role
• L. Create a security configuration mapping for the additional IAM roles to Active Directory user groups for each team.

Answer: C

NEW QUESTION 12
A data analyst is designing a solution to interactively query datasets with SQL using a JDBC connection. Users will join data stored in Amazon S3 in Apache ORC format with data stored in Amazon Elasticsearch Service (Amazon ES) and Amazon Aurora MySQL.
Which solution will provide the MOST up-to-date results?

• A. Use AWS Glue jobs to ETL data from Amazon ES and Aurora MySQL to Amazon S3. Query the data with Amazon Athena.
• B. Use Amazon DMS to stream data from Amazon ES and Aurora MySQL to Amazon Redshif
• C. Query the data with Amazon Redshift.
• D. Query all the datasets in place with Apache Spark SQL running on an AWS Glue developer endpoint.
• E. Query all the datasets in place with Apache Presto running on Amazon EMR.

Answer: C

NEW QUESTION 13
A company analyzes historical data and needs to query data that is stored in Amazon S3. New data is
generated daily as .csv files that are stored in Amazon S3. The company’s analysts are using Amazon Athena to perform SQL queries against a recent subset of the overall data. The amount of data that is ingested into Amazon S3 has increased substantially over time, and the query latency also has increased.
Which solutions could the company implement to improve query performance? (Choose two.)

• A. Use MySQL Workbench on an Amazon EC2 instance, and connect to Athena by using a JDBC or ODBC connecto
• B. Run the query from MySQL Workbench instead of Athena directly.
• C. Use Athena to extract the data and store it in Apache Parquet format on a daily basi
• D. Query the extracted data.
• E. Run a daily AWS Glue ETL job to convert the data files to Apache Parquet and to partition the converted file
• F. Create a periodic AWS Glue crawler to automatically crawl the partitioned data on a daily basis.
• G. Run a daily AWS Glue ETL job to compress the data files by using the .gzip forma
• H. Query the compressed data.
• I. Run a daily AWS Glue ETL job to compress the data files by using the .lzo forma
• J. Query the compressed data.

Answer: BC

NEW QUESTION 14
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. EMR File System (EMRFS) for storage
• B. Hadoop Distributed File System (HDFS) for storage
• C. AWS Glue Data Catalog as the metastore for Apache Hive
• D. MySQL database on the master node as the metastore for Apache Hive
• E. Multiple master nodes in a single Availability Zone
• F. Multiple master nodes in multiple Availability Zones

Answer: ACE

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 15
A manufacturing company wants to create an operational analytics dashboard to visualize metrics from equipment in near-real time. The company uses Amazon Kinesis Data Streams to stream the data to other applications. The dashboard must automatically refresh every 5 seconds. A data analytics specialist must design a solution that requires the least possible implementation effort.
Which solution meets these requirements?

• A. Use Amazon Kinesis Data Firehose to store the data in Amazon S3. Use Amazon QuickSight to build the dashboard.
• B. Use Apache Spark Streaming on Amazon EMR to read the data in near-real tim
• C. Develop a custom application for the dashboard by using D3.js.
• D. Use Amazon Kinesis Data Firehose to push the data into an Amazon Elasticsearch Service (Amazon ES) cluste
• E. Visualize the data by using a Kibana dashboard.
• F. Use AWS Glue streaming ETL to store the data in Amazon S3. Use Amazon QuickSight to build the dashboard.

Answer: B

NEW QUESTION 16
An ecommerce company is migrating its business intelligence environment from on premises to the AWS Cloud. The company will use Amazon Redshift in a public subnet and Amazon QuickSight. The tables already are loaded into Amazon Redshift and can be accessed by a SQL tool.
The company starts QuickSight for the first time. During the creation of the data source, a data analytics specialist enters all the information and tries to validate the connection. An error with the following message occurs: “Creating a connection to your data source timed out.”
How should the data analytics specialist resolve this error?

• A. Grant the SELECT permission on Amazon Redshift tables.
• B. Add the QuickSight IP address range into the Amazon Redshift security group.
• C. Create an IAM role for QuickSight to access Amazon Redshift.
• D. Use a QuickSight admin user for creating the dataset.

Answer: A

Explanation:
Connection to the database times out
Your client connection to the database appears to hang or time out when running long queries, such as a COPY command. In this case, you might observe that the Amazon Redshift console displays that the query has completed, but the client tool itself still appears to be running the query. The results of the query might be missing or incomplete depending on when the connection stopped.

NEW QUESTION 17
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. Load all the data into the new table and grant the auditing group permission to read from the tabl
• B. Load all the data except for the columns containing sensitive data into a second tabl
• C. Grant the appropriate users read-only permissions to the second table.
• D. Load all the data into the new table and grant the auditing group permission to read from the tabl
• E. Use the GRANT SQL command to allow read-only access to a subset of columns to the appropriate users.
• F. Load all the data into the new table and grant all users read-only permissions to non-sensitive columns.Attach an IAM policy to the auditing group with explicit ALLOW access to the sensitive data columns.
• G. Load all the data into the new table and grant the auditing group permission to read from the table.Create a view of the new table that contains all the columns, except for those considered sensitive, and grant the appropriate users read-only permissions to the table.

Answer: B

Explanation:
https://aws.amazon.com/blogs/big-data/achieve-finer-grained-data-security-with-column-level-access-control-in

NEW QUESTION 18
A large ride-sharing company has thousands of drivers globally serving millions of unique customers every day. The company has decided to migrate an existing data mart to Amazon Redshift. The existing schema includes the following tables.
A trips fact table for information on completed rides. A drivers dimension table for driver profiles. A customers fact table holding customer profile information.
The company analyzes trip details by date and destination to examine profitability by region. The drivers data rarely changes. The customers data frequently changes.
What table design provides optimal query performance?

• A. Use DISTSTYLE KEY (destination) for the trips table and sort by dat
• B. Use DISTSTYLE ALL for the drivers and customers tables.
• C. Use DISTSTYLE EVEN for the trips table and sort by dat
• D. Use DISTSTYLE ALL for the drivers table.Use DISTSTYLE EVEN for the customers table.
• E. Use DISTSTYLE KEY (destination) for the trips table and sort by dat
• F. Use DISTSTYLE ALL for the drivers tabl
• G. Use DISTSTYLE EVEN for the customers table.
• H. Use DISTSTYLE EVEN for the drivers table and sort by dat
• I. Use DISTSTYLE ALL for both fact tables.

Answer: C

Explanation:
https://www.matillion.com/resources/blog/aws-redshift-performance-choosing-the-right-distribution-styles/#:~:t https://docs.aws.amazon.com/redshift/latest/dg/c_best-practices-best-dist-key.html

NEW QUESTION 19
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