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BDS-C00: AWS Certified Big Data - Specialty

AWS Certified Big Data - Specialty
Vendor:

Amazon

AWS Certified Big Data - Specialty Exam Questions: 85
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The AWS Certified Big Data – Specialty (BDS-C00) exam is a crucial certification for anyone aiming to advance their career in big data on AWS. Our topic is your ultimate resource for BDS-C00 practice test shared by individuals who have successfully passed the exam. These practice tests provide real-world scenarios and invaluable insights to help you ace your preparation.

Why Use BDS-C00 Practice Test?

  • Real Exam Experience: Our practice test accurately replicates the format and difficulty of the actual AWS BDS-C00 exam, providing you with a realistic preparation experience.

  • Identify Knowledge Gaps: Practicing with these tests helps you identify areas where you need more study, allowing you to focus your efforts effectively.

  • Boost Confidence: Regular practice with exam-like questions builds your confidence and reduces test anxiety.

  • Track Your Progress: Monitor your performance over time to see your improvement and adjust your study plan accordingly.

Key Features of BDS-C00 Practice Test:

  • Up-to-Date Content: Our community ensures that the questions are regularly updated to reflect the latest exam objectives and technology trends.

  • Detailed Explanations: Each question comes with detailed explanations, helping you understand the correct answers and learn from any mistakes.

  • Comprehensive Coverage: The practice test covers all key topics of the AWS BDS-C00 exam, including big data concepts, data processing, and AWS big data services.

  • Customizable Practice: Create your own practice sessions based on specific topics or difficulty levels to tailor your study experience to your needs.

Exam number: BDS-C00

Exam name: AWS Certified Big Data – Specialty

Length of test: 180 minutes

Exam format: Multiple-choice and multiple-response questions.

Exam language: English

Number of questions in the actual exam: Maximum of 65 questions

Passing score: 750/1000

Use the member-shared AWS BDS-C00 Practice Test to ensure you’re fully prepared for your certification exam. Start practicing today and take a significant step towards achieving your certification goals!

Related questions

A company has several teams of analysts. Each team of analysts has their own cluster. The teams need to run SQL queries using Hive, Spark-SQL, and Presto with Amazon EMR. The company needs to enable a centralized metadata layer to expose the Amazon S3 objects as tables to the analysts. Which approach meets the requirement for a centralized metadata layer?

A.
EMRFS consistent view with a common Amazon DynamoDB table
A.
EMRFS consistent view with a common Amazon DynamoDB table
Answers
B.
Bootstrap action to change the Hive Metastore to an Amazon RDS database
B.
Bootstrap action to change the Hive Metastore to an Amazon RDS database
Answers
C.
s3distcp with the outputManifest option to generate RDS DDL
C.
s3distcp with the outputManifest option to generate RDS DDL
Answers
D.
Naming scheme support with automatic partition discovery from Amazon S3
D.
Naming scheme support with automatic partition discovery from Amazon S3
Answers
Suggested answer: A
asked 16/09/2024
AXEL AXELOPOULOS
41 questions

A web-hosting company is building a web analytics tool to capture clickstream data from all of the websites hosted within its platform and to provide near-realtime business intelligence. This entire system is built on AWS services. The webhosting company is interested in using Amazon Kinesis to collect this data and perform sliding window analytics.

What is the most reliable and fault-tolerant technique to get each website to send data to Amazon Kinesis with every click?

A.
After receiving a request, each web server sends it to Amazon Kinesis using the Amazon Kinesis PutRecord API. Use the sessionID as a partition key and setup a loop to retry until a success response is received.
A.
After receiving a request, each web server sends it to Amazon Kinesis using the Amazon Kinesis PutRecord API. Use the sessionID as a partition key and setup a loop to retry until a success response is received.
Answers
B.
After receiving a request, each web server sends it to Amazon Kinesis using the Amazon Kinesis Producer Library .addRecords method.
B.
After receiving a request, each web server sends it to Amazon Kinesis using the Amazon Kinesis Producer Library .addRecords method.
Answers
C.
Each web server buffers the requests until the count reaches 500 and sends them to Amazon Kinesis using the Amazon Kinesis PutRecord API call.
C.
Each web server buffers the requests until the count reaches 500 and sends them to Amazon Kinesis using the Amazon Kinesis PutRecord API call.
Answers
D.
After receiving a request, each web server sends it to Amazon Kinesis using the Amazon Kinesis PutRecord API. Use the exponential back-off algorithm forretries until a successful response is received.
D.
After receiving a request, each web server sends it to Amazon Kinesis using the Amazon Kinesis PutRecord API. Use the exponential back-off algorithm forretries until a successful response is received.
Answers
Suggested answer: A
asked 16/09/2024
Yuri Shpovlov
40 questions

A travel website needs to present a graphical quantitative summary of its daily bookings to website visitors for marketing purposes. The website has millions of visitors per day, but wants to control costs by implementing the least-expensive solution for this visualization. What is the most cost-effective solution?

A.
Generate a static graph with a transient EMR cluster daily, and store in an Amazon S3.
A.
Generate a static graph with a transient EMR cluster daily, and store in an Amazon S3.
Answers
B.
Generate a graph using MicroStrategy backed by a transient EMR cluster.
B.
Generate a graph using MicroStrategy backed by a transient EMR cluster.
Answers
C.
Implement a Jupyter front-end provided by a continuously running EMR cluster leveraging spot instances for task nodes.
C.
Implement a Jupyter front-end provided by a continuously running EMR cluster leveraging spot instances for task nodes.
Answers
D.
Implement a Zeppelin application that runs on a long-running EMR cluster.
D.
Implement a Zeppelin application that runs on a long-running EMR cluster.
Answers
Suggested answer: A
asked 16/09/2024
Said Jabri
40 questions

A media advertising company handles a large number of real-time messages sourced from over 200 websites in real time. Processing latency must be kept low. Based on calculations, a 60-shard Amazon Kinesis stream is more than sufficient to handle the maximum data throughput, even with traffic spikes. The company also uses an Amazon Kinesis Client Library (KCL) application running on Amazon Elastic Compute Cloud (EC2) managed by an Auto Scaling group. Amazon CloudWatch indicates an average of 25% CPU and a modest level of network traffic across all running servers.

The company reports a 150% to 200% increase in latency of processing messages from Amazon Kinesis during peak times. There are NO reports of delay from the sites publishing to Amazon Kinesis.

What is the appropriate solution to address the latency?

A.
Increase the number of shards in the Amazon Kinesis stream to 80 for greater concurrency.
A.
Increase the number of shards in the Amazon Kinesis stream to 80 for greater concurrency.
Answers
B.
Increase the size of the Amazon EC2 instances to increase network throughput.
B.
Increase the size of the Amazon EC2 instances to increase network throughput.
Answers
C.
Increase the minimum number of instances in the Auto Scaling group.
C.
Increase the minimum number of instances in the Auto Scaling group.
Answers
D.
Increase Amazon DynamoDB throughput on the checkpoint table.
D.
Increase Amazon DynamoDB throughput on the checkpoint table.
Answers
Suggested answer: D
asked 16/09/2024
Tracy Nicholas
33 questions

A company uses Amazon Redshift for its enterprise data warehouse. A new on-premises PostgreSQL OLTP DB must be integrated into the data warehouse. Each table in the PostgreSQL DB has an indexed last_modified timestamp column. The data warehouse has a staging layer to load source data into the data warehouse environment for further processing.

The data lag between the source PostgreSQL DB and the Amazon Redshift staging layer should NOT exceed four hours. What is the most efficient technique to meet these requirements?

A.
Create a DBLINK on the source DB to connect to Amazon Redshift. Use a PostgreSQL trigger on the source table to capture the new insert/update/deleteevent and execute the event on the Amazon Redshift staging table.
A.
Create a DBLINK on the source DB to connect to Amazon Redshift. Use a PostgreSQL trigger on the source table to capture the new insert/update/deleteevent and execute the event on the Amazon Redshift staging table.
Answers
B.
Use a PostgreSQL trigger on the source table to capture the new insert/update/delete event and write it to Amazon Kinesis Streams. Use a KCL applicationto execute the event on the Amazon Redshift staging table.
B.
Use a PostgreSQL trigger on the source table to capture the new insert/update/delete event and write it to Amazon Kinesis Streams. Use a KCL applicationto execute the event on the Amazon Redshift staging table.
Answers
C.
Extract the incremental changes periodically using a SQL query. Upload the changes to multiple Amazon Simple Storage Service (S3) objects, and run theCOPY command to load to the Amazon Redshift staging layer.
C.
Extract the incremental changes periodically using a SQL query. Upload the changes to multiple Amazon Simple Storage Service (S3) objects, and run theCOPY command to load to the Amazon Redshift staging layer.
Answers
D.
Extract the incremental changes periodically using a SQL query. Upload the changes to a single Amazon Simple Storage Service (S3) object, and run theCOPY command to load to the Amazon Redshift staging layer.
D.
Extract the incremental changes periodically using a SQL query. Upload the changes to a single Amazon Simple Storage Service (S3) object, and run theCOPY command to load to the Amazon Redshift staging layer.
Answers
Suggested answer: C
asked 16/09/2024
Evgeniy Lyashonkov
34 questions

An organization's data warehouse contains sales data for reporting purposes. data governance policies prohibit staff from accessing the customers' credit card numbers.

How can these policies be adhered to and still allow a Data Scientist to group transactions that use the same credit card number?

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An organization is currently using an Amazon EMR long-running cluster with the latest Amazon EMR release for analytic jobs and is storing data as external tables on Amazon S3.

The company needs to launch multiple transient EMR clusters to access the same tables concurrently, but the metadata about the Amazon S3 external tables are defined and stored on the long-running cluster.

Which solution will expose the Hive metastore with the LEAST operational effort?

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Multiple rows in an Amazon Redshift table were accidentally deleted. A System Administrator is restoring the table from the most recent snapshot. The snapshot contains all rows that were in the table before the deletion.

What is the SIMPLEST solution to restore the table without impacting users?

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A company with a support organization needs support engineers to be able to search historic cases to provide fast responses on new issues raised. The company has forwarded all support messages into an Amazon Kinesis Stream. This meets a company objective of using only managed services to reduce operational overhead.

The company needs an appropriate architecture that allows support engineers to search on historic cases and find similar issues and their associated responses. Which AWS Lambda action is most appropriate?

A.
Ingest and index the content into an Amazon Elasticsearch domain.
A.
Ingest and index the content into an Amazon Elasticsearch domain.
Answers
B.
Stem and tokenize the input and store the results into Amazon ElastiCache.
B.
Stem and tokenize the input and store the results into Amazon ElastiCache.
Answers
C.
Write data as JSON into Amazon DynamoDB with primary and secondary indexes.
C.
Write data as JSON into Amazon DynamoDB with primary and secondary indexes.
Answers
D.
Aggregate feedback in Amazon S3 using a columnar format with partitioning.
D.
Aggregate feedback in Amazon S3 using a columnar format with partitioning.
Answers
Suggested answer: A
asked 16/09/2024
Wendie Canez
39 questions

A company that provides economics data dashboards needs to be able to develop software to display rich, interactive, data-driven graphics that run in web browsers and leverages the full stack of web standards (HTML, SVG, and CSS). Which technology provides the most appropriate support for this requirements?

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