aws_DAS-C01_2024.3.5_814/1000

164問 • 1年前

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Question #: 1 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A financial services company needs to aggregate daily stock trade data from the exchanges into a data store. The company requires that data be streamed directly into the data store, but also occasionally allows data to be modified using SQL. The solution should integrate complex, analytic queries running with minimal latency. The solution must provide a business intelligence dashboard that enables viewing of the top contributors to anomalies in stock prices. Which solution meets the company's requirements?

C. Use Amazon Kinesis Data Firehose to stream data to Amazon Redshift. Use Amazon Redshift as a data source for Amazon QuickSight to create a business intelligence dashboard.

Question #: 2 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A financial company hosts a data lake in Amazon S3 and a data warehouse on an Amazon Redshift cluster. The company uses Amazon QuickSight to build dashboards and wants to secure access from its on-premises Active Directory to Amazon QuickSight. How should the data be secured?

A. Use an Active Directory connector and single sign-on (SSO) in a corporate network environment.

Question #: 3 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] 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?

D. 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 nodes. Create a secondary EMR HBase read-replica cluster in a separate Availability Zone. Point both clusters to the same HBase root directory in the same Amazon S3 bucket.

Question #: 4 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A software company hosts an application on AWS, and new features are released weekly. As part of the application testing process, a solution must be developed that analyzes logs from each Amazon EC2 instance to ensure that the application is working as expected after each deployment. The collection and analysis solution should be highly available with the ability to display new information with minimal delays. Which method should the company use to collect and analyze the logs?

D. Use Amazon CloudWatch subscriptions to get access to a real-time feed of logs and have the logs delivered to Amazon Kinesis Data Streams to further push the data to Amazon OpenSearch Service (Amazon Elasticsearch Service) and OpenSearch Dashboards (Kibana).

Question #: 5 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A data analyst is using AWS Glue to organize, cleanse, validate, and format a 200 GB dataset. The data analyst triggered the job to run with the Standard worker type. After 3 hours, the AWS Glue job status is still RUNNING. Logs from the job run show no error codes. The data analyst wants to improve the job execution time without overprovisioning. Which actions should the data analyst take?

B. Enable job metrics in AWS Glue to estimate the number of data processing units (DPUs). Based on the profiled metrics, increase the value of the maximum capacity job parameter.

Question #: 6 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A company has a business unit uploading .csv files to an Amazon S3 bucket. The company's data platform team has set up an AWS Glue crawler to do discovery, and create tables and schemas. An AWS Glue job writes processed data from the created tables to an Amazon Redshift database. The AWS Glue job handles column mapping and creating the Amazon Redshift table appropriately. When the AWS Glue job is rerun for any reason in a day, duplicate records are introduced into the Amazon Redshift table. Which solution will update the Redshift table without duplicates when jobs are rerun?

A. Modify the AWS Glue job to copy the rows into a staging table. Add SQL commands to replace the existing rows in the main table as postactions in the DynamicFrameWriter class.

Question #: 7 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A streaming application is reading data from Amazon Kinesis Data Streams and immediately writing the data to an Amazon S3 bucket every 10 seconds. The application is reading data from hundreds of shards. The batch interval cannot be changed due to a separate requirement. The data is being accessed by Amazon Athena. Users are seeing degradation in query performance as time progresses. Which action can help improve query performance?

A. Merge the files in Amazon S3 to form larger files.

Question #: 8 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A company uses Amazon OpenSearch Service (Amazon Elasticsearch Service) to store and analyze its website clickstream data. The company ingests 1 TB of data daily using Amazon Kinesis Data Firehose and stores one day's worth of data in an Amazon ES cluster. The company has very slow query performance on the Amazon ES index and occasionally sees errors from Kinesis Data Firehose when attempting to write to the index. The Amazon ES cluster has 10 nodes running a single index and 3 dedicated master nodes. Each data node has 1.5 TB of Amazon EBS storage attached and the cluster is configured with 1,000 shards. Occasionally, JVMMemoryPressure errors are found in the cluster logs. Which solution will improve the performance of Amazon ES?

C. Decrease the number of Amazon ES shards for the index.

Question #: 9 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] 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. Create a daily job in AWS Glue to UNLOAD records older than 13 months to Amazon S3 and delete those records from Amazon Redshift. Create an external table in Amazon Redshift to point to the S3 location. Use Amazon Redshift Spectrum to join to data that is older than 13 months.

Question #: 10 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] 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?

D. Run the AWS Glue crawler from an AWS Lambda function triggered by an S3:ObjectCreated:* event notification on the S3 bucket.

Question #: 11 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A company that produces network devices has millions of users. Data is collected from the devices on an hourly basis and stored in an Amazon S3 data lake. The company runs analyses on the last 24 hours of data flow logs for abnormality detection and to troubleshoot and resolve user issues. The company also analyzes historical logs dating back 2 years to discover patterns and look for improvement opportunities. The data flow logs contain many metrics, such as date, timestamp, source IP, and target IP. There are about 10 billion events every day. How should this data be stored for optimal performance?

A. In Apache ORC partitioned by date and sorted by source IP

Question #: 12 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A banking company is currently using an Amazon Redshift cluster with dense storage (DS) nodes to store sensitive data. An audit found that the cluster is unencrypted. Compliance requirements state that a database with sensitive data must be encrypted through a hardware security module (HSM) with automated key rotation. Which combination of steps is required to achieve compliance? (Choose two.)

A. Set up a trusted connection with HSM using a client and server certificate with automatic key rotation., C. Create a new HSM-encrypted Amazon Redshift cluster and migrate the data to the new cluster.

Question #: 13 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A company is planning to do a proof of concept for a machine learning (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?

C. Ingest data into Amazon S3 using AWS DMS. Use AWS Glue to perform data curation and store the data in Amazon S3 for ML processing.

Question #: 14 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A US-based sneaker retail company launched its global website. All the transaction data is stored in Amazon RDS and curated historic transaction data is stored in Amazon Redshift in the us-east-1 Region. The business intelligence (BI) team wants to enhance the user experience by providing a dashboard for sneaker trends. The BI team decides to use Amazon QuickSight to render the website dashboards. During development, a team in Japan provisioned Amazon QuickSight in ap- northeast-1. The team is having difficulty connecting Amazon QuickSight from ap-northeast-1 to Amazon Redshift in us-east-1. Which solution will solve this issue and meet the requirements?

D. Create a new security group for Amazon Redshift in us-east-1 with an inbound rule authorizing access from the appropriate IP address range for the Amazon QuickSight servers in ap-northeast-1.

Question #: 15 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] An airline has .csv-formatted data stored in Amazon S3 with an AWS Glue Data Catalog. Data analysts want to join this data with call center data stored in Amazon Redshift as part of a dally batch process. The Amazon Redshift cluster is already under a heavy load. The solution must be managed, serverless, well- functioning, and minimize the load on the existing Amazon Redshift cluster. The solution should also require minimal effort and development activity. Which solution meets these requirements?

C. Create an external table using Amazon Redshift Spectrum for the call center data and perform the join with Amazon Redshift.

Question #: 16 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A data analyst is using Amazon QuickSight for data visualization across multiple datasets generated by applications. Each application stores files within a separate Amazon S3 bucket. AWS Glue Data Catalog is used as a central catalog across all application data in Amazon S3. A new application stores its data within a separate S3 bucket. After updating the catalog to include the new application data source, the data analyst created a new Amazon QuickSight data source from an Amazon Athena table, but the import into SPICE failed. How should the data analyst resolve the issue?

B. Edit the permissions for the new S3 bucket from within the Amazon QuickSight console.

Question #: 17 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] 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?

B. 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.

Question #: 18 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] 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?

B. Run the AWS Glue crawler in us-west-2 to catalog datasets in all Regions. Once the data is crawled, run Athena queries in us-west-2.

Question #: 19 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A large company receives files from external parties in Amazon EC2 throughout the day. At the end of the day, the files are combined into a single file, compressed into a gzip file, and uploaded to Amazon S3. The total size of all the files is close to 100 GB daily. Once the files are uploaded to Amazon S3, an AWS Batch program executes a COPY command to load the files into an Amazon Redshift cluster. Which program modification will accelerate the COPY process?

B. Split the number of files so they are equal to a multiple of the number of slices in the Amazon Redshift cluster. Gzip and upload the files to Amazon S3. Run the COPY command on the files.

Question #: 20 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] 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?

C. Use DISTSTYLE KEY (destination) for the trips table and sort by date. Use DISTSTYLE ALL for the drivers table. Use DISTSTYLE EVEN for the customers table.

Question #: 21 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] 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?

B. 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 bucket. Add the service role for the EMR cluster EC2 instances to the trust policies for the additional IAM roles. Create a security configuration mapping for the additional IAM roles to Active Directory user groups for each team.

Question #: 22 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A company is planning to create a data lake in Amazon S3. The company wants to create tiered storage based on access patterns and cost objectives. The solution must include support for JDBC connections from legacy clients, metadata management that allows federation for access control, and batch-based ETL using PySpark and Scala. Operational management should be limited. Which combination of components can meet these requirements? (Choose three.)

A. AWS Glue Data Catalog for metadata management, C. AWS Glue for Scala-based ETL, E. Amazon Athena for querying data in Amazon S3 using JDBC drivers

Question #: 23 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] 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. Use an AWS Glue ETL job to compress, partition, and convert the data into a columnar data format. Use Athena to query the processed dataset. Configure a lifecycle policy to move the processed data into the Amazon S3 Standard-Infrequent Access (S3 Standard-IA) storage class 5 years after object creation. Configure a second lifecycle policy to move the raw data into Amazon S3 Glacier for long-term archival 7 days after object creation.

Question #: 24 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] An energy company collects voltage data in real time from sensors that are attached to buildings. The company wants to receive notifications when a sequence of two voltage drops is detected within 10 minutes of a sudden voltage increase at the same building. All notifications must be delivered as quickly as possible. The system must be highly available. The company needs a solution that will automatically scale when this monitoring feature is implemented in other cities. The notification system is subscribed to an Amazon Simple Notification Service (Amazon SNS) topic for remediation. Which solution will meet these requirements?

D. Create an Amazon Kinesis data stream to capture the incoming sensor data. Create another stream for notifications. Set up AWS Application Auto Scaling on both streams. Create an Amazon Kinesis Data Analytics for Java application to detect the known event sequence, and add a message to the message stream Configure an AWS Lambda function to poll the message stream and publish to the SNS topic.

Question #: 25 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] 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?

D. Send the data to Amazon Kinesis Data Streams and configure an Amazon Kinesis Analytics for Java application as the consumer. The application will consume the data and process it to identify potential playback issues. Persist the raw data to Amazon S3.

Question #: 26 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] 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?

D. Incrementally copy data from Amazon RDS to Amazon S3. Load and store the most recent 6 months of data in Amazon Redshift. Configure an Amazon Redshift Spectrum table to connect to all historical data.

Question #: 27 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A company leverages Amazon Athena for ad-hoc queries against data stored in Amazon S3. The company wants to implement additional controls to separate query execution and query history among users, teams, or applications running in the same AWS account to comply with internal security policies. Which solution meets these requirements?

B. Create an Athena workgroup for each given use case, apply tags to the workgroup, and create an IAM policy using the tags to apply appropriate permissions to the workgroup.

Question #: 28 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A company wants to use an automatic machine learning (ML) Random Cut Forest (RCF) algorithm to visualize complex real-world scenarios, such as detecting seasonality and trends, excluding outers, and imputing missing values. The team working on this project is non-technical and is looking for an out-of-the-box solution that will require the LEAST amount of management overhead. Which solution will meet these requirements?

B. Use Amazon QuickSight to visualize the data and then use ML-powered forecasting to forecast the key business metrics.

Question #: 29 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A retail company's data analytics team recently created multiple product sales analysis dashboards for the average selling price per product using Amazon QuickSight. The dashboards were created from .csv files uploaded to Amazon S3. The team is now planning to share the dashboards with the respective external product owners by creating individual users in Amazon QuickSight. For compliance and governance reasons, restricting access is a key requirement. The product owners should view only their respective product analysis in the dashboard reports. Which approach should the data analytics team take to allow product owners to view only their products in the dashboard?

D. Create dataset rules with row-level security.

Question #: 30 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A company has developed an Apache Hive script to batch process data stared in Amazon S3. The script needs to run once every day and store the output in Amazon S3. The company tested the script, and it completes within 30 minutes on a small local three-node cluster. Which solution is the MOST cost-effective for scheduling and executing the script?

A. Create an AWS Lambda function to spin up an Amazon EMR cluster with a Hive execution step. Set KeepJobFlowAliveWhenNoSteps to false and disable the termination protection flag. Use Amazon CloudWatch Events to schedule the Lambda function to run daily.

Question #: 31 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] 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?

B. Split large .csv files, then use a COPY command to load data into Amazon Redshift.

Question #: 32 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A company has a data warehouse in Amazon Redshift that is approximately 500 TB in size. New data is imported every few hours and read-only queries are run throughout the day and evening. There is a particularly heavy load with no writes for several hours each morning on business days. During those hours, some queries are queued and take a long time to execute. The company needs to optimize query execution and avoid any downtime. What is the MOST cost-effective solution?

A. Enable concurrency scaling in the workload management (WLM) queue.

Question #: 33 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] 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.

Question #: 34 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A company stores its sales and marketing data that includes personally identifiable information (PII) in Amazon S3. The company allows its analysts to launch their own Amazon EMR cluster and run analytics reports with the data. To meet compliance requirements, the company must ensure the data is not publicly accessible throughout this process. A data engineer has secured Amazon S3 but must ensure the individual EMR clusters created by the analysts are not exposed to the public internet. Which solution should the data engineer to meet this compliance requirement with LEAST amount of effort?

C. Enable the block public access setting for Amazon EMR at the account level before any EMR cluster is created.

Question #: 35 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A financial company uses Amazon S3 as its data lake and has set up a data warehouse using a multi-node Amazon Redshift cluster. The data files in the data lake are organized in folders based on the data source of each data file. All the data files are loaded to one table in the Amazon Redshift cluster using a separate COPY command for each data file location. With this approach, loading all the data files into Amazon Redshift takes a long time to complete. Users want a faster solution with little or no increase in cost while maintaining the segregation of the data files in the S3 data lake. Which solution meets these requirements?

D. Create a manifest file that contains the data file locations and issue a COPY command to load the data into Amazon Redshift.

Question #: 36 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A company's marketing team has asked for help in identifying a high performing long-term storage service for their data based on the following requirements: ✑ The data size is approximately 32 TB uncompressed. ✑ There is a low volume of single-row inserts each day. ✑ There is a high volume of aggregation queries each day. ✑ Multiple complex joins are performed. ✑ The queries typically involve a small subset of the columns in a table. Which storage service will provide the MOST performant solution?

B. Amazon Redshift

Question #: 37 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A technology company is creating a dashboard that will visualize and analyze time-sensitive data. The data will come in through Amazon Kinesis Data Firehose with the butter interval set to 60 seconds. The dashboard must support near-real-time data. Which visualization solution will meet these requirements?

A. Select Amazon Elasticsearch Service (Amazon ES) as the endpoint for Kinesis Data Firehose. Set up a Kibana dashboard using the data in Amazon ES with the desired analyses and visualizations.

Question #: 38 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] 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?

D. Create instance group configurations for core and task nodes. Create an automatic scaling policy to scale out the instance groups based on the Amazon CloudWatch YARNMemoryAvailablePercentage metric. Create an automatic scaling policy to scale in the instance groups based on the CloudWatch YARNMemoryAvailablePercentage metric.

Question #: 39 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A media company has been performing analytics on log data generated by its applications. There has been a recent increase in the number of concurrent analytics jobs running, and the overall performance of existing jobs is decreasing as the number of new jobs is increasing. The partitioned data is stored in Amazon S3 One Zone-Infrequent Access (S3 One Zone-IA) and the analytic processing is performed on Amazon EMR clusters using the EMR File System (EMRFS) with consistent view enabled. A data analyst has determined that it is taking longer for the EMR task nodes to list objects in Amazon S3. Which action would MOST likely increase the performance of accessing log data in Amazon S3?

C. Increase the read capacity units (RCUs) for the shared Amazon DynamoDB table.

Question #: 40 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A company has developed several AWS Glue jobs to validate and transform its data from Amazon S3 and load it into Amazon RDS for MySQL in batches once every day. The ETL jobs read the S3 data using a DynamicFrame. Currently, the ETL developers are experiencing challenges in processing only the incremental data on every run, as the AWS Glue job processes all the S3 input data on each run. Which approach would allow the developers to solve the issue with minimal coding effort?

B. Enable job bookmarks on the AWS Glue jobs.

Question #: 41 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A mortgage company has a microservice for accepting payments. This microservice uses the Amazon DynamoDB encryption client with AWS KMS managed keys to encrypt the sensitive data before writing the data to DynamoDB. The finance team should be able to load this data into Amazon Redshift and aggregate the values within the sensitive fields. The Amazon Redshift cluster is shared with other data analysts from different business units. Which steps should a data analyst take to accomplish this task efficiently and securely?

B. Create an AWS Lambda function to process the DynamoDB stream. Save the output to a restricted S3 bucket for the finance team. Create a finance table in Amazon Redshift that is accessible to the finance team only. Use the COPY command with the IAM role that has access to the KMS key to load the data from S3 to the finance table.

Question #: 42 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] 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. Use AWS Glue to connect to the data source using JDBC Drivers. Ingest incremental records only using job bookmarks.

Question #: 43 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] An Amazon Redshift database contains sensitive user data. Logging is necessary to meet compliance requirements. The logs must contain database authentication attempts, connections, and disconnections. The logs must also contain each query run against the database and record which database user ran each query. Which steps will create the required logs?

C. Enable audit logging for Amazon Redshift using the AWS Management Console or the AWS CLI.

Question #: 44 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A company that monitors weather conditions from remote construction sites is setting up a solution to collect temperature data from the following two weather stations. ✑ Station A, which has 10 sensors ✑ Station B, which has five sensors These weather stations were placed by onsite subject-matter experts. Each sensor has a unique ID. The data collected from each sensor will be collected using Amazon Kinesis Data Streams. Based on the total incoming and outgoing data throughput, a single Amazon Kinesis data stream with two shards is created. Two partition keys are created based on the station names. During testing, there is a bottleneck on data coming from Station A, but not from Station B. Upon review, it is confirmed that the total stream throughput is still less than the allocated Kinesis Data Streams throughput. How can this bottleneck be resolved without increasing the overall cost and complexity of the solution, while retaining the data collection quality requirements?

C. Modify the partition key to use the sensor ID instead of the station name.

Question #: 45 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] 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 into Amazon S3 and query it with Amazon S3 Select.

Question #: 46 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A retail company is building its data warehouse solution using Amazon Redshift. As a part of that effort, the company is loading hundreds of files into the fact table created in its Amazon Redshift cluster. The company wants the solution to achieve the highest throughput and optimally use cluster resources when loading data into the company's fact table. How should the company meet these requirements?

D. Use a single COPY command to load the data into the Amazon Redshift cluster.

Question #: 47 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] 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?

D. Query all the datasets in place with Apache Presto running on Amazon EMR.

Question #: 48 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] 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.

Question #: 49 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] 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?

C. Set up an individual AWS account for the central data lake. Use AWS Lake Formation to catalog the cross-account locations. On each individual S3 bucket, modify the bucket policy to grant S3 permissions to the Lake Formation service-linked role. Use Lake Formation permissions to add fine-grained access controls to allow senior analysts to view specific tables and columns.

Question #: 50 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A company wants to improve user satisfaction for its smart home system by adding more features to its recommendation engine. Each sensor asynchronously pushes its nested JSON data into Amazon Kinesis Data Streams using the Kinesis Producer Library (KPL) in Java. Statistics from a set of failed sensors showed that, when a sensor is malfunctioning, its recorded data is not always sent to the cloud. The company needs a solution that offers near-real-time analytics on the data from the most updated sensors. Which solution enables the company to meet these requirements?

B. Update the sensors code to use the PutRecord/PutRecords call from the Kinesis Data Streams API with the AWS SDK for Java. Use Kinesis Data Analytics to enrich the data based on a company-developed anomaly detection SQL script. Direct the output of KDA application to a Kinesis Data Firehose delivery stream, enable the data transformation feature to flatten the JSON file, and set the Kinesis Data Firehose destination to an Amazon Elasticsearch Service cluster.

Question #: 51 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A global company has different sub-organizations, and each sub-organization sells its products and services in various countries. The company's senior leadership wants to quickly identify which sub-organization is the strongest performer in each country. All sales data is stored in Amazon S3 in Parquet format. Which approach can provide the visuals that senior leadership requested with the least amount of effort?

A. Use Amazon QuickSight with Amazon Athena as the data source. Use heat maps as the visual type.

Question #: 52 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] 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?

B. 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.

Question #: 53 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A mobile gaming company wants to capture data from its gaming app and make the data available for analysis immediately. The data record size will be approximately 20 KB. The company is concerned about achieving optimal throughput from each device. Additionally, the company wants to develop a data stream processing application with dedicated throughput for each consumer. Which solution would achieve this goal?

A. Have the app call the PutRecords API to send data to Amazon Kinesis Data Streams. Use the enhanced fan-out feature while consuming the data.

Question #: 54 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A marketing company wants to improve its reporting and business intelligence capabilities. During the planning phase, the company interviewed the relevant stakeholders and discovered that: ✑ The operations team reports are run hourly for the current month's data. ✑ The sales team wants to use multiple Amazon QuickSight dashboards to show a rolling view of the last 30 days based on several categories. The sales team also wants to view the data as soon as it reaches the reporting backend. ✑ The finance team's reports are run daily for last month's data and once a month for the last 24 months of data. Currently, there is 400 TB of data in the system with an expected additional 100 TB added every month. The company is looking for a solution that is as cost- effective as possible. Which solution meets the company's requirements?

B. Store the last 2 months of data in Amazon Redshift and the rest of the months in Amazon S3. Set up an external schema and table for Amazon Redshift Spectrum. Configure Amazon QuickSight with Amazon Redshift as the data source.

Question #: 55 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A media company wants to perform machine learning and analytics on the data residing in its Amazon S3 data lake. There are two data transformation requirements that will enable the consumers within the company to create reports: ✑ Daily transformations of 300 GB of data with different file formats landing in Amazon S3 at a scheduled time. ✑ One-time transformations of terabytes of archived data residing in the S3 data lake. Which combination of solutions cost-effectively meets the company's requirements for transforming the data? (Choose three.)

A. For daily incoming data, use AWS Glue crawlers to scan and identify the schema., D. For daily incoming data, use AWS Glue workflows with AWS Glue jobs to perform transformations., E. For archived data, use Amazon EMR to perform data transformations.

Question #: 56 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A hospital uses wearable medical sensor devices to collect data from patients. The hospital is architecting a near-real-time solution that can ingest the data securely at scale. The solution should also be able to remove the patient's protected health information (PHI) from the streaming data and store the data in durable storage. Which solution meets these requirements with the least operational overhead?

D. Ingest the data using Amazon Kinesis Data Firehose to write the data to Amazon S3. Implement a transformation AWS Lambda function that parses the sensor data to remove all PHI.

Question #: 57 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A company is migrating its existing on-premises ETL jobs to Amazon EMR. The code consists of a series of jobs written in Java. The company needs to reduce overhead for the system administrators without changing the underlying code. Due to the sensitivity of the data, compliance requires that the company use root device volume encryption on all nodes in the cluster. Corporate standards require that environments be provisioned though AWS CloudFormation when possible. Which solution satisfies these requirements?

C. Create a custom AMI with encrypted root device volumes. Configure Amazon EMR to use the custom AMI using the CustomAmild property in the CloudFormation template.

Question #: 58 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A transportation company uses IoT sensors attached to trucks to collect vehicle data for its global delivery fleet. The company currently sends the sensor data in small .csv files to Amazon S3. The files are then loaded into a 10-node Amazon Redshift cluster with two slices per node and queried using both Amazon Athena and Amazon Redshift. The company wants to optimize the files to reduce the cost of querying and also improve the speed of data loading into the Amazon Redshift cluster. Which solution meets these requirements?

D. Use AWS Glue to convert the files from .csv to Apache Parquet to create 20 Parquet files. COPY the files into Amazon Redshift and query the files with Athena from Amazon S3.

Question #: 59 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] An online retail company with millions of users around the globe wants to improve its ecommerce analytics capabilities. Currently, clickstream data is uploaded directly to Amazon S3 as compressed files. Several times each day, an application running on Amazon EC2 processes the data and makes search options and reports available for visualization by editors and marketers. The company wants to make website clicks and aggregated data available to editors and marketers in minutes to enable them to connect with users more effectively. Which options will help meet these requirements in the MOST efficient way? (Choose two.)

A. Use Amazon Kinesis Data Firehose to upload compressed and batched clickstream records to Amazon OpenSearch Service (Amazon Elasticsearch Service)., D. Use OpenSearch Dashboards (Kibana) to aggregate, filter, and visualize the data stored in Amazon OpenSearch Service (Amazon Elasticsearch Service). Refresh content performance dashboards in near-real time.

Question #: 60 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A company is streaming its high-volume billing data (100 MBps) to Amazon Kinesis Data Streams. A data analyst partitioned the data on account_id to ensure that all records belonging to an account go to the same Kinesis shard and order is maintained. While building a custom consumer using the Kinesis Java SDK, the data analyst notices that, sometimes, the messages arrive out of order for account_id. Upon further investigation, the data analyst discovers the messages that are out of order seem to be arriving from different shards for the same account_id and are seen when a stream resize runs. What is an explanation for this behavior and what is the solution?

D. The consumer is not processing the parent shard completely before processing the child shards after a stream resize. The data analyst should process the parent shard completely first before processing the child shards.

Question #: 61 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A media analytics company consumes a stream of social media posts. The posts are sent to an Amazon Kinesis data stream partitioned on user_id. An AWS Lambda function retrieves the records and validates the content before loading the posts into an Amazon Elasticsearch cluster. The validation process needs to receive the posts for a given user in the order they were received. A data analyst has noticed that, during peak hours, the social media platform posts take more than an hour to appear in the Elasticsearch cluster. What should the data analyst do reduce this latency?

D. Configure multiple Lambda functions to process the stream.

Question #: 62 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A company launched a service that produces millions of messages every day and uses Amazon Kinesis Data Streams as the streaming service. The company uses the Kinesis SDK to write data to Kinesis Data Streams. A few months after launch, a data analyst found that write performance is significantly reduced. The data analyst investigated the metrics and determined that Kinesis is throttling the write requests. The data analyst wants to address this issue without significant changes to the architecture. Which actions should the data analyst take to resolve this issue? (Choose two.)

C. Increase the number of shards in the stream using the UpdateShardCount API., D. Choose partition keys in a way that results in a uniform record distribution across shards.

Question #: 63 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A smart home automation company must efficiently ingest and process messages from various connected devices and sensors. The majority of these messages are comprised of a large number of small files. These messages are ingested using Amazon Kinesis Data Streams and sent to Amazon S3 using a Kinesis data stream consumer application. The Amazon S3 message data is then passed through a processing pipeline built on Amazon EMR running scheduled PySpark jobs. The data platform team manages data processing and is concerned about the efficiency and cost of downstream data processing. They want to continue to use PySpark. Which solution improves the efficiency of the data processing jobs and is well architected?

D. Set up AWS Glue Python jobs to merge the small data files in Amazon S3 into larger files and transform them to Apache Parquet format. Migrate the downstream PySpark jobs from Amazon EMR to AWS Glue.

Question #: 64 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A large financial company is running its ETL process. Part of this process is to move data from Amazon S3 into an Amazon Redshift cluster. The company wants to use the most cost-efficient method to load the dataset into Amazon Redshift. Which combination of steps would meet these requirements? (Choose two.)

A. Use the COPY command with the manifest file to load data into Amazon Redshift., C. Use temporary staging tables during the loading process.

Question #: 65 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A university intends to use Amazon Kinesis Data Firehose to collect JSON-formatted batches of water quality readings in Amazon S3. The readings are from 50 sensors scattered across a local lake. Students will query the stored data using Amazon Athena to observe changes in a captured metric over time, such as water temperature or acidity. Interest has grown in the study, prompting the university to reconsider how data will be stored. Which data format and partitioning choices will MOST significantly reduce costs? (Choose two.)

B. Partition the data by year, month, and day., D. Store the data in Apache Parquet format using Snappy compression.

Question #: 66 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A healthcare company uses AWS data and analytics tools to collect, ingest, and store electronic health record (EHR) data about its patients. The raw EHR data is stored in Amazon S3 in JSON format partitioned by hour, day, and year and is updated every hour. The company wants to maintain the data catalog and metadata in an AWS Glue Data Catalog to be able to access the data using Amazon Athena or Amazon Redshift Spectrum for analytics. When defining tables in the Data Catalog, the company has the following requirements: ✑ Choose the catalog table name and do not rely on the catalog table naming algorithm. ✑ Keep the table updated with new partitions loaded in the respective S3 bucket prefixes. Which solution meets these requirements with minimal effort?

C. Use the AWS Glue API CreateTable operation to create a table in the Data Catalog. Create an AWS Glue crawler and specify the table as the source.

Question #: 67 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A large university has adopted a strategic goal of increasing diversity among enrolled students. The data analytics team is creating a dashboard with data visualizations to enable stakeholders to view historical trends. All access must be authenticated using Microsoft Active Directory. All data in transit and at rest must be encrypted. Which solution meets these requirements?

B. Amazon QuickSight Enterprise edition configured to perform identity federation using SAML 2.0 and the default encryption settings.

Question #: 68 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] An airline has been collecting metrics on flight activities for analytics. A recently completed proof of concept demonstrates how the company provides insights to data analysts to improve on-time departures. The proof of concept used objects in Amazon S3, which contained the metrics in .csv format, and used Amazon Athena for querying the data. As the amount of data increases, the data analyst wants to optimize the storage solution to improve query performance. Which options should the data analyst use to improve performance as the data lake grows? (Choose three.)

C. Compress the objects to reduce the data transfer I/O., D. Use an S3 bucket in the same Region as Athena., F. Preprocess the .csv data to Apache Parquet to reduce I/O by fetching only the data blocks needed for predicates.

Question #: 69 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] 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?

B. Create a customer master key (CMK) in AWS KMS. Assign the CMK an alias. Enable server-side encryption on the Kinesis data stream using the CMK alias as the KMS master key.

Question #: 70 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A company wants to enrich application logs in near-real-time and use the enriched dataset for further analysis. The application is running on Amazon EC2 instances across multiple Availability Zones and storing its logs using Amazon CloudWatch Logs. The enrichment source is stored in an Amazon DynamoDB table. Which solution meets the requirements for the event collection and enrichment?

A. Use a CloudWatch Logs subscription to send the data to Amazon Kinesis Data Firehose. Use AWS Lambda to transform the data in the Kinesis Data Firehose delivery stream and enrich it with the data in the DynamoDB table. Configure Amazon S3 as the Kinesis Data Firehose delivery destination.

Question #: 71 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] 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?

B. Load all the data into the new table and grant the auditing group permission to read from the table. Use the GRANT SQL command to allow read-only access to a subset of columns to the appropriate users.

Question #: 72 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A banking company wants to collect large volumes of transactional data using Amazon Kinesis Data Streams for real-time analytics. The company uses PutRecord to send data to Amazon Kinesis, and has observed network outages during certain times of the day. The company wants to obtain exactly once semantics for the entire processing pipeline. What should the company do to obtain these characteristics?

A. Design the application so it can remove duplicates during processing be embedding a unique ID in each record.

Question #: 73 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A company's data analyst needs to ensure that queries run in Amazon Athena cannot scan more than a prescribed amount of data for cost control purposes. Queries that exceed the prescribed threshold must be canceled immediately. What should the data analyst do to achieve this?

B. For each workgroup, set the control limit for each query to the prescribed threshold.

Question #: 74 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A marketing company is using Amazon EMR clusters for its workloads. The company manually installs third-party libraries on the clusters by logging in to the master nodes. A data analyst needs to create an automated solution to replace the manual process. Which options can fulfill these requirements? (Choose two.)

A. Place the required installation scripts in Amazon S3 and execute them using custom bootstrap actions., E. Launch an Amazon EC2 instance with Amazon Linux and install the required third-party libraries on the instance. Create an AMI and use that AMI to create the EMR cluster.

Question #: 75 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A data engineering team within a shared workspace company wants to build a centralized logging system for all weblogs generated by the space reservation system. The company has a fleet of Amazon EC2 instances that process requests for shared space reservations on its website. The data engineering team wants to ingest all weblogs into a service that will provide a near-real-time search engine. The team does not want to manage the maintenance and operation of the logging system. Which solution allows the data engineering team to efficiently set up the web logging system within AWS?

B. Set up the Amazon CloudWatch agent to stream weblogs to CloudWatch logs and subscribe the Amazon Kinesis Data Firehose delivery stream to CloudWatch. Choose Amazon OpenSearch Service (Amazon Elasticsearch Service) as the end destination of the weblogs.

Question #: 76 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] 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?

B. Keep the data from the last 90 days in Amazon Redshift. Move data older than 90 days to Amazon S3 and store it in Apache Parquet format partitioned by date. Then use Amazon Redshift Spectrum for the additional analysis.

Question #: 77 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A bank operates in a regulated environment. The compliance requirements for the country in which the bank operates say that customer data for each state should only be accessible by the bank's employees located in the same state. Bank employees in one state should NOT be able to access data for customers who have provided a home address in a different state. The bank's marketing team has hired a data analyst to gather insights from customer data for a new campaign being launched in certain states. Currently, data linking each customer account to its home state is stored in a tabular .csv file within a single Amazon S3 folder in a private S3 bucket. The total size of the S3 folder is 2 GB uncompressed. Due to the country's compliance requirements, the marketing team is not able to access this folder. The data analyst is responsible for ensuring that the marketing team gets one-time access to customer data for their campaign analytics project, while being subject to all the compliance requirements and controls. Which solution should the data analyst implement to meet the desired requirements with the LEAST amount of setup effort?

D. Load tabular data from Amazon S3 to Amazon QuickSight Enterprise edition by directly importing it as a data source. Use the built-in row-level security feature in Amazon QuickSight to provide marketing employees with appropriate data access under compliance controls. Delete Amazon QuickSight data sources after the project is complete.

Question #: 78 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] An online gaming company is using an Amazon Kinesis Data Analytics SQL application with a Kinesis data stream as its source. The source sends three non-null fields to the application: player_id, score, and us_5_digit_zip_code. A data analyst has a .csv mapping file that maps a small number of us_5_digit_zip_code values to a territory code. The data analyst needs to include the territory code, if one exists, as an additional output of the Kinesis Data Analytics application. How should the data analyst meet this requirement while minimizing costs?

C. Store the mapping file in an Amazon S3 bucket and configure it as a reference data source for the Kinesis Data Analytics application. Change the SQL query in the application to include a join to the reference table and add the territory code field to the SELECT columns.

Question #: 79 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A company has collected more than 100 TB of log files in the last 24 months. The files are stored as raw text in a dedicated Amazon S3 bucket. Each object has a key of the form year-month-day_log_HHmmss.txt where HHmmss represents the time the log file was initially created. A table was created in Amazon Athena that points to the S3 bucket. One-time queries are run against a subset of columns in the table several times an hour. A data analyst must make changes to reduce the cost of running these queries. Management wants a solution with minimal maintenance overhead. Which combination of steps should the data analyst take to meet these requirements? (Choose three.)

B. Add a key prefix of the form date=year-month-day/ to the S3 objects to partition the data., C. Convert the log files to Apache Parquet format., F. Drop and recreate the table with the PARTITIONED BY clause. Run the MSCK REPAIR TABLE statement.

Question #: 80 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A company has an application that ingests streaming data. The company needs to analyze this stream over a 5-minute timeframe to evaluate the stream for anomalies with Random Cut Forest (RCF) and summarize the current count of status codes. The source and summarized data should be persisted for future use. Which approach would enable the desired outcome while keeping data persistence costs low?

B. Ingest the data stream with Amazon Kinesis Data Streams. Have a Kinesis Data Analytics application evaluate the stream over a 5-minute window using the RCF function and summarize the count of status codes. Persist the source and results to Amazon S3 through output delivery to Kinesis Data Firehouse.

Question #: 81 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] An online retailer needs to deploy a product sales reporting solution. The source data is exported from an external online transaction processing (OLTP) system for reporting. Roll-up data is calculated each day for the previous day's activities. The reporting system has the following requirements: ✑ Have the daily roll-up data readily available for 1 year. ✑ After 1 year, archive the daily roll-up data for occasional but immediate access. ✑ The source data exports stored in the reporting system must be retained for 5 years. Query access will be needed only for re-evaluation, which may occur within the first 90 days. Which combination of actions will meet these requirements while keeping storage costs to a minimum? (Choose two.)

B. Store the source data initially in the Amazon S3 Glacier storage class. Apply a lifecycle configuration that changes the storage class from Amazon S3 Glacier to Amazon S3 Glacier Deep Archive 90 days after creation, and then deletes the data 5 years after creation., D. Store the daily roll-up data initially in the Amazon S3 Standard storage class. Apply a lifecycle configuration that changes the storage class to Amazon S3 Standard-Infrequent Access (S3 Standard-IA) 1 year after data creation.

Question #: 82 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] 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.

Question #: 83 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A data analytics specialist is building an automated ETL ingestion pipeline using AWS Glue to ingest compressed files that have been uploaded to an Amazon S3 bucket. The ingestion pipeline should support incremental data processing. Which AWS Glue feature should the data analytics specialist use to meet this requirement?

C. Job bookmarks

Question #: 84 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A telecommunications company is looking for an anomaly-detection solution to identify fraudulent calls. The company currently uses Amazon Kinesis to stream voice call records in a JSON format from its on-premises database to Amazon S3. The existing dataset contains voice call records with 200 columns. To detect fraudulent calls, the solution would need to look at 5 of these columns only. The company is interested in a cost-effective solution using AWS that requires minimal effort and experience in anomaly-detection algorithms. Which solution meets these requirements?

A. Use an AWS Glue job to transform the data from JSON to Apache Parquet. Use AWS Glue crawlers to discover the schema and build the AWS Glue Data Catalog. Use Amazon Athena to create a table with a subset of columns. Use Amazon QuickSight to visualize the data and then use Amazon QuickSight machine learning-powered anomaly detection.

Question #: 85 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] An online retailer is rebuilding its inventory management system and inventory reordering system to automatically reorder products by using Amazon Kinesis Data Streams. The inventory management system uses the Kinesis Producer Library (KPL) to publish data to a stream. The inventory reordering system uses the Kinesis Client Library (KCL) to consume data from the stream. The stream has been configured to scale as needed. Just before production deployment, the retailer discovers that the inventory reordering system is receiving duplicated data. Which factors could be causing the duplicated data? (Choose two.)

A. The producer has a network-related timeout., C. There was a change in the number of shards, record processors, or both.

Question #: 86 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A large retailer has successfully migrated to an Amazon S3 data lake architecture. The company's marketing team is using Amazon Redshift and Amazon QuickSight to analyze data, and derive and visualize insights. To ensure the marketing team has the most up-to-date actionable information, a data analyst implements nightly refreshes of Amazon Redshift using terabytes of updates from the previous day. After the first nightly refresh, users report that half of the most popular dashboards that had been running correctly before the refresh are now running much slower. Amazon CloudWatch does not show any alerts. What is the MOST likely cause for the performance degradation?

D. The nightly data refreshes left the dashboard tables in need of a vacuum operation that could not be automatically performed by Amazon Redshift due to ongoing user workloads.

Question #: 87 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A marketing company is storing its campaign response data in Amazon S3. A consistent set of sources has generated the data for each campaign. The data is saved into Amazon S3 as .csv files. A business analyst will use Amazon Athena to analyze each campaign's data. The company needs the cost of ongoing data analysis with Athena to be minimized. Which combination of actions should a data analytics specialist take to meet these requirements? (Choose two.)

A. Convert the .csv files to Apache Parquet., C. Partition the data by campaign.

Question #: 88 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] An online retail company is migrating its reporting system to AWS. The company's legacy system runs data processing on online transactions using a complex series of nested Apache Hive queries. Transactional data is exported from the online system to the reporting system several times a day. Schemas in the files are stable between updates. A data analyst wants to quickly migrate the data processing to AWS, so any code changes should be minimized. To keep storage costs low, the data analyst decides to store the data in Amazon S3. It is vital that the data from the reports and associated analytics is completely up to date based on the data in Amazon S3. Which solution meets these requirements?

A. Create an AWS Glue Data Catalog to manage the Hive metadata. Create an AWS Glue crawler over Amazon S3 that runs when data is refreshed to ensure that data changes are updated. Create an Amazon EMR cluster and use the metadata in the AWS Glue Data Catalog to run Hive processing queries in Amazon EMR.

Question #: 89 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A media company is using Amazon QuickSight dashboards to visualize its national sales data. The dashboard is using a dataset with these fields: ID, date, time_zone, city, state, country, longitude, latitude, sales_volume, and number_of_items. To modify ongoing campaigns, the company wants an interactive and intuitive visualization of which states across the country recorded a significantly lower sales volume compared to the national average. Which addition to the company's QuickSight dashboard will meet this requirement?

A. A geospatial color-coded chart of sales volume data across the country.

Question #: 90 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A company hosts an on-premises PostgreSQL database that contains historical data. An internal legacy application uses the database for read-only activities. The company's business team wants to move the data to a data lake in Amazon S3 as soon as possible and enrich the data for analytics. The company has set up an AWS Direct Connect connection between its VPC and its on-premises network. A data analytics specialist must design a solution that achieves the business team's goals with the least operational overhead. Which solution meets these requirements?

D. Configure an AWS Glue crawler to use a JDBC connection to catalog the data in the on-premises database. Use an AWS Glue job to enrich the data and save the result to Amazon S3 in Apache Parquet format. Use Amazon Athena to query the data.

Question #: 91 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A medical company has a system with sensor devices that read metrics and send them in real time to an Amazon Kinesis data stream. The Kinesis data stream has multiple shards. The company needs to calculate the average value of a numeric metric every second and set an alarm for whenever the value is above one threshold or below another threshold. The alarm must be sent to Amazon Simple Notification Service (Amazon SNS) in less than 30 seconds. Which architecture meets these requirements?

D. Use an Amazon Kinesis Data Analytics application to read from the Kinesis data stream and calculate the average per second. Send the results to an AWS Lambda function that sends the alarm to Amazon SNS.

Question #: 92 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] An IoT company wants to release a new device that will collect data to track sleep overnight on an intelligent mattress. Sensors will send data that will be uploaded to an Amazon S3 bucket. About 2 MB of data is generated each night for each bed. Data must be processed and summarized for each user, and the results need to be available as soon as possible. Part of the process consists of time windowing and other functions. Based on tests with a Python script, every run will require about 1 GB of memory and will complete within a couple of minutes. Which solution will run the script in the MOST cost-effective way?

A. AWS Lambda with a Python script

Question #: 93 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A company wants to provide its data analysts with uninterrupted access to the data in its Amazon Redshift cluster. All data is streamed to an Amazon S3 bucket with Amazon Kinesis Data Firehose. An AWS Glue job that is scheduled to run every 5 minutes issues a COPY command to move the data into Amazon Redshift. The amount of data delivered is uneven throughout the day, and cluster utilization is high during certain periods. The COPY command usually completes within a couple of seconds. However, when load spike occurs, locks can exist and data can be missed. Currently, the AWS Glue job is configured to run without retries, with timeout at 5 minutes and concurrency at 1. How should a data analytics specialist configure the AWS Glue job to optimize fault tolerance and improve data availability in the Amazon Redshift cluster?

A. Increase the number of retries. Decrease the timeout value. Increase the job concurrency.

Question #: 94 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A retail company leverages Amazon Athena for ad-hoc queries against an AWS Glue Data Catalog. The data analytics team manages the data catalog and data access for the company. The data analytics team wants to separate queries and manage the cost of running those queries by different workloads and teams. Ideally, the data analysts want to group the queries run by different users within a team, store the query results in individual Amazon S3 buckets specific to each team, and enforce cost constraints on the queries run against the Data Catalog. Which solution meets these requirements?

C. Create Athena workgroups for each team within the company. Set up IAM workgroup policies that control user access and actions on the workgroup resources.

Question #: 95 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A manufacturing company uses Amazon S3 to store its data. The company wants to use AWS Lake Formation to provide granular-level security on those data assets. The data is in Apache Parquet format. The company has set a deadline for a consultant to build a data lake. How should the consultant create the MOST cost-effective solution that meets these requirements?

B. To create the data catalog, run an AWS Glue crawler on the existing Parquet data. Register the Amazon S3 path and then apply permissions through Lake Formation to provide granular-level security.

Question #: 96 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A company has an application that uses the Amazon Kinesis Client Library (KCL) to read records from a Kinesis data stream. After a successful marketing campaign, the application experienced a significant increase in usage. As a result, a data analyst had to split some shards in the data stream. When the shards were split, the application started throwing an ExpiredIteratorExceptions error sporadically. What should the data analyst do to resolve this?

C. Increase the provisioned write capacity units assigned to the stream's Amazon DynamoDB table.

Question #: 97 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] 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.

Question #: 98 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] 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, C. AWS Glue Data Catalog as the metastore for Apache Hive, E. Multiple master nodes in a single Availability Zone

Question #: 99 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A retail company wants to use Amazon QuickSight to generate dashboards for web and in-store sales. A group of 50 business intelligence professionals will develop and use the dashboards. Once ready, the dashboards will be shared with a group of 1,000 users. The sales data comes from different stores and is uploaded to Amazon S3 every 24 hours. The data is partitioned by year and month, and is stored in Apache Parquet format. The company is using the AWS Glue Data Catalog as its main data catalog and Amazon Athena for querying. The total size of the uncompressed data that the dashboards query from at any point is 200 GB. Which configuration will provide the MOST cost-effective solution that meets these requirements?

C. Use QuickSight Enterprise edition. Configure 50 author users and 1,000 reader users. Configure an Athena data source and import the data into SPICE. Automatically refresh every 24 hours.

100

Question #: 100 Topic #: 1 [All AWS Certified Data Analytics - Specialty Questions] A central government organization is collecting events from various internal applications using Amazon Managed Streaming for Apache Kafka (Amazon MSK). The organization has configured a separate Kafka topic for each application to separate the data. For security reasons, the Kafka cluster has been configured to only allow TLS encrypted data and it encrypts the data at rest. A recent application update showed that one of the applications was configured incorrectly, resulting in writing data to a Kafka topic that belongs to another application. This resulted in multiple errors in the analytics pipeline as data from different applications appeared on the same topic. After this incident, the organization wants to prevent applications from writing to a topic different than the one they should write to. Which solution meets these requirements with the least amount of effort?

C. Use Kafka ACLs and configure read and write permissions for each topic. Use the distinguished name of the clients' TLS certificates as the principal of the ACL.

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