In this blog, we talk about big data and data analytics; we also give you the last updated top 20 AWS Certified Data Analytics – Specialty Questions and Answers Dumps
I- The AWS Certified Data Analytics – Specialty (DAS-C01) examination is intended for individuals who perform in a data analytics-focused role. This exam validates an examinee’s comprehensive understanding of using AWS services to design, build, secure, and maintain analytics solutions that provide insight from data.
The AWS Certified Data Analytics – Specialty (DAS-C01) covers the following domains:
Domain 1: Collection 18%
Domain 2: Storage and Data Management 22%
Domain 3: Processing 24%
Domain 4: Analysis and Visualization 18%
Domain 5: Security 18%
Below are the Top 20 AWS Certified Data Analytics – Specialty Questions and Answers Dumps and References –
Question1: What combination of services do you need for the following requirements: accelerate petabyte-scale data transfers, load streaming data, and the ability to create scalable, private connections. Select the correct answer order.
A) Snowball, Kinesis Firehose, Direct Connect
B) Data Migration Services, Kinesis Firehose, Direct Connect
C) Snowball, Data Migration Services, Direct Connect
D) Snowball, Direct Connection, Kinesis Firehose
Reference1: Big Data Analytics Options
Reference1: Relationalize PySpark
Question 3: There is a five-day car rally race across Europe. The race coordinators are using a Kinesis stream and IoT sensors to monitor the movement of the cars. Each car has a sensor and data is getting back to the stream with the default stream settings. On the last day of the rally, data is sent to S3. When you go to interpret the data in S3, there is only data for the last day and nothing for the first 4 days. Which of the following is the most probable cause of this?
A) You did not have versioning enabled and would need to create individual buckets to prevent the data from being overwritten.
B) Data records are only accessible for a default of 24 hours from the time they are added to a stream.
C) One of the sensors failed, so there was no data to record.
D) You needed to use EMR to send the data to S3; Kinesis Streams are only compatible with DynamoDB.
Reference3: Kinesis Extended Reading
Question 4: A publisher website captures user activity and sends clickstream data to Amazon Kinesis Data Streams. The publisher wants to design a cost-effective solution to process the data to create a timeline of user activity within a session. The solution must be able to scale depending on the number of active sessions.
Which solution meets these requirements?
A) Include a variable in the clickstream data from the publisher website to maintain a counter for the number of active user sessions. Use a timestamp for the partition key for the stream. Configure the consumer application to read the data from the stream and change the number of processor threads based upon the counter. Deploy the consumer application on Amazon EC2 instances in an EC2 Auto Scaling group.
B) Include a variable in the clickstream to maintain a counter for each user action during their session. Use the action type as the partition key for the stream. Use the Kinesis Client Library (KCL) in the consumer application to retrieve the data from the stream and perform the processing. Configure the consumer application to read the data from the stream and change the number of processor threads based upon the
counter. Deploy the consumer application on AWS Lambda.
C) Include a session identifier in the clickstream data from the publisher website and use as the partition key for the stream. Use the Kinesis Client Library (KCL) in the consumer application to retrieve the data from the stream and perform the processing. Deploy the consumer application on Amazon EC2 instances in an
EC2 Auto Scaling group. Use an AWS Lambda function to reshard the stream based upon Amazon CloudWatch alarms.
D) Include a variable in the clickstream data from the publisher website to maintain a counter for the number of active user sessions. Use a timestamp for the partition key for the stream. Configure the consumer application to read the data from the stream and change the number of processor threads based upon the counter. Deploy the consumer application on AWS Lambda.
Reference4: UpdateShardCount API
Question 5: Your company has two batch processing applications that consume financial data about the day’s stock transactions. Each transaction needs to be stored durably and guarantee that a record of each application is delivered so the audit and billing batch processing applications can process the data. However, the two applications run separately and several hours apart and need access to the same transaction information. After reviewing the transaction information for the day, the information no longer needs to be stored. What is the best way to architect this application?
A) Use SQS for storing the transaction messages; when the billing batch process performs first and consumes the message, write the code in a way that does not remove the message after consumed, so it is available for the audit application several hours later. The audit application can consume the SQS message and remove it from the queue when completed.
B) Use Kinesis to store the transaction information. The billing application will consume data from the stream and the audit application can consume the same data several hours later.
C) Store the transaction information in a DynamoDB table. The billing application can read the rows while the audit application will read the rows then remove the data.
D) Use SQS for storing the transaction messages. When the billing batch process consumes each message, have the application create an identical message and place it in a different SQS for the audit application to use several hours later.
SQS would make this more difficult because the data does not need to persist after a full day.
Reference5: Amazon Kinesis
Question 6: A company is currently using Amazon DynamoDB as the database for a user support application. The company is developing a new version of the application that will store a PDF file for each support case ranging in size from 1–10 MB. The file should be retrievable whenever the case is accessed in the application.
How can the company store the file in the MOST cost-effective manner?
A) Store the file in Amazon DocumentDB and the document ID as an attribute in the DynamoDB table.
B) Store the file in Amazon S3 and the object key as an attribute in the DynamoDB table.
C) Split the file into smaller parts and store the parts as multiple items in a separate DynamoDB table.
D) Store the file as an attribute in the DynamoDB table using Base64 encoding.
Question 7: Your client has a web app that emits multiple events to Amazon Kinesis Streams for reporting purposes. Critical events need to be immediately captured before processing can continue, but informational events do not need to delay processing. What solution should your client use to record these types of events without unnecessarily slowing the application?
A) Log all events using the Kinesis Producer Library.
B) Log critical events using the Kinesis Producer Library, and log informational events using the PutRecords API method.
C) Log critical events using the PutRecords API method, and log informational events using the Kinesis Producer Library.
D) Log all events using the PutRecords API method.
Reference7: PutRecords API
Question 8: You work for a start-up that tracks commercial delivery trucks via GPS. You receive coordinates that are transmitted from each delivery truck once every 6 seconds. You need to process these coordinates in near real-time from multiple sources and load them into Elasticsearch without significant technical overhead to maintain. Which tool should you use to digest the data?
A) Amazon SQS
B) Amazon EMR
C) AWS Data Pipeline
D) Amazon Kinesis Firehose
Reference8: Amazon Kinesis Firehose
Question 9: A company needs to implement a near-real-time fraud prevention feature for its ecommerce site. User and order details need to be delivered to an Amazon SageMaker endpoint to flag suspected fraud. The amount of input data needed for the inference could be as much as 1.5 MB.
Which solution meets the requirements with the LOWEST overall latency?
A) Create an Amazon Managed Streaming for Kafka cluster and ingest the data for each order into a topic. Use a Kafka consumer running on Amazon EC2 instances to read these messages and invoke the Amazon SageMaker endpoint.
B) Create an Amazon Kinesis Data Streams stream and ingest the data for each order into the stream. Create an AWS Lambda function to read these messages and invoke the Amazon SageMaker endpoint.
C) Create an Amazon Kinesis Data Firehose delivery stream and ingest the data for each order into the stream. Configure Kinesis Data Firehose to deliver the data to an Amazon S3 bucket. Trigger an AWS Lambda function with an S3 event notification to read the data and invoke the Amazon SageMaker endpoint.
D) Create an Amazon SNS topic and publish the data for each order to the topic. Subscribe the Amazon SageMaker endpoint to the SNS topic.
Reference9: Amazon Managed Streaming for Kafka cluster
Question 10: You need to filter and transform incoming messages coming from a smart sensor you have connected with AWS. Once messages are received, you need to store them as time series data in DynamoDB. Which AWS service can you use?
A) IoT Device Shadow Service
D) IoT Rules Engine
Reference10: The IoT rules engine
Question 11: A media company is migrating its on-premises legacy Hadoop cluster with its associated data processing scripts and workflow to an Amazon EMR environment running the latest Hadoop release. The developers want to reuse the Java code that was written for data processing jobs for the on-premises cluster.
Which approach meets these requirements?
A) Deploy the existing Oracle Java Archive as a custom bootstrap action and run the job on the EMR cluster.
B) Compile the Java program for the desired Hadoop version and run it using a CUSTOM_JAR step on the EMR cluster.
C) Submit the Java program as an Apache Hive or Apache Spark step for the EMR cluster.
D) Use SSH to connect the master node of the EMR cluster and submit the Java program using the AWS CLI.
Reference11: Automating analytics workflows on EMR
Question 12: You currently have databases running on-site and in another data center off-site. What service allows you to consolidate to one database in Amazon?
A) AWS Kinesis
B) AWS Database Migration Service
C) AWS Data Pipeline
D) AWS RDS Aurora
Question 13: An online retail company wants to perform analytics on data in large Amazon S3 objects using Amazon EMR. An Apache Spark job repeatedly queries the same data to populate an analytics dashboard. The analytics team wants to minimize the time to load the data and create the dashboard.
Which approaches could improve the performance? (Select TWO.)
A) Copy the source data into Amazon Redshift and rewrite the Apache Spark code to create analytical reports by querying Amazon Redshift.
B) Copy the source data from Amazon S3 into Hadoop Distributed File System (HDFS) using s3distcp.
C) Load the data into Spark DataFrames.
D) Stream the data into Amazon Kinesis and use the Kinesis Connector Library (KCL) in multiple Spark jobs to perform analytical jobs.
E) Use Amazon S3 Select to retrieve the data necessary for the dashboards from the S3 objects.
Reference13: Spark DataFrames
Question 14: You have been hired as a consultant to provide a solution to integrate a client’s on-premises data center to AWS. The customer requires a 300 Mbps dedicated, private connection to their VPC. Which AWS tool do you need?
A) VPC peering
B) Data Pipeline
C) Direct Connect
Reference14: Direct Connect
Question 15: Your organization has a variety of different services deployed on EC2 and needs to efficiently send application logs over to a central system for processing and analysis. They’ve determined it is best to use a managed AWS service to transfer their data from the EC2 instances into Amazon S3 and they’ve decided to use a solution that will do what?
A) Installs the AWS Direct Connect client on all EC2 instances and uses it to stream the data directly to S3.
B) Leverages the Kinesis Agent to send data to Kinesis Data Streams and output that data in S3.
C) Ingests the data directly from S3 by configuring regular Amazon Snowball transactions.
D) Leverages the Kinesis Agent to send data to Kinesis Firehose and output that data in S3.
Reference15: Kinesis Firehose
Question 16: A data engineer needs to create a dashboard to display social media trends during the last hour of a large company event. The dashboard needs to display the associated metrics with a latency of less than 1 minute.
Which solution meets these requirements?
A) Publish the raw social media data to an Amazon Kinesis Data Firehose delivery stream. Use Kinesis Data Analytics for SQL Applications to perform a sliding window analysis to compute the metrics and output the results to a Kinesis Data Streams data stream. Configure an AWS Lambda function to save the stream data to an Amazon DynamoDB table. Deploy a real-time dashboard hosted in an Amazon S3 bucket to read and display the metrics data stored in the DynamoDB table.
B) Publish the raw social media data to an Amazon Kinesis Data Firehose delivery stream. Configure the stream to deliver the data to an Amazon Elasticsearch Service cluster with a buffer interval of 0 seconds. Use Kibana to perform the analysis and display the results.
C) Publish the raw social media data to an Amazon Kinesis Data Streams data stream. Configure an AWS Lambda function to compute the metrics on the stream data and save the results in an Amazon S3 bucket. Configure a dashboard in Amazon QuickSight to query the data using Amazon Athena and display the results.
D) Publish the raw social media data to an Amazon SNS topic. Subscribe an Amazon SQS queue to the topic. Configure Amazon EC2 instances as workers to poll the queue, compute the metrics, and save the results to an Amazon Aurora MySQL database. Configure a dashboard in Amazon QuickSight to query the data in Aurora and display the results.
Question 17: A real estate company is receiving new property listing data from its agents through .csv files every day and storing these files in Amazon S3. The data analytics team created an Amazon QuickSight visualization report that uses a dataset imported from the S3 files. The data analytics team wants the visualization report to reflect the current data up to the previous day. How can a data analyst meet these requirements?
A) Schedule an AWS Lambda function to drop and re-create the dataset daily.
B) Configure the visualization to query the data in Amazon S3 directly without loading the data into SPICE.
C) Schedule the dataset to refresh daily.
D) Close and open the Amazon QuickSight visualization.
Reference17: Amazon QuickSight and SPICE
Question 18: You need to migrate data to AWS. It is estimated that the data transfer will take over a month via the current AWS Direct Connect connection your company has set up. Which AWS tool should you use?
A) Establish additional Direct Connect connections.
B) Use Data Pipeline to migrate the data in bulk to S3.
C) Use Kinesis Firehose to stream all new and existing data into S3.
Question 19: You currently have an on-premises Oracle database and have decided to leverage AWS and use Aurora. You need to do this as quickly as possible. How do you achieve this?
A) It is not possible to migrate an on-premises database to AWS at this time.
B) Use AWS Data Pipeline to create a target database, migrate the database schema, set up the data replication process, initiate the full load and a subsequent change data capture and apply, and conclude with a switchover of your production environment to the new database once the target database is caught up with the source database.
C) Use AWS Database Migration Services and create a target database, migrate the database schema, set up the data replication process, initiate the full load and a subsequent change data capture and apply, and conclude with a switch-over of your production environment to the new database once the target database is caught up with the source database.
D) Use AWS Glue to crawl the on-premises database schemas and then migrate them into AWS with Data Pipeline jobs.
Question 20: A financial company uses Amazon EMR for its analytics workloads. During the company’s annual security audit, the security team determined that none of the EMR clusters’ root volumes are encrypted. The security team recommends the company encrypt its EMR clusters’ root volume as soon as possible.
Which solution would meet these requirements?
A) Enable at-rest encryption for EMR File System (EMRFS) data in Amazon S3 in a security configuration. Re-create the cluster using the newly created security configuration.
B) Specify local disk encryption in a security configuration. Re-create the cluster using the newly created security configuration.
C) Detach the Amazon EBS volumes from the master node. Encrypt the EBS volume and attach it back to the master node.
D) Re-create the EMR cluster with LZO encryption enabled on all volumes.
Reference20: EMR Cluster Local disk encryption
1- Djamga Big Data – Data Analytics Youtube Playlist
III- Big Data – Data Analytics Jobs:
IV- DATA ANALYTICS Q&A: