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BDS-C00: AWS Certified Big Data - Specialty

Amazon BDS-C00 Exam Questions

Name: Amazon BDS-C00 Exam
Brand: Pass4Success
SKU: BDS-C00
Price: 69.00 USD
Availability: InStock
Rating: 4.9 (188 reviews)

Status: RETIRED

Exam Name: Amazon AWS Certified Big Data - Specialty Exam

Exam Code: BDS-C00

Related Certification(s): Amazon Specialty Certification

Certification Provider: Amazon

Actual Exam Duration: 170 Minutes

Number of BDS-C00 practice questions in our database: 264 (updated: 19-08-2026)

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Hafsa Hassan

6 days ago

Processing items tended to be performance tuning scenarios for Spark on EMR or Glue ETL jobs, where the right partitioning, shuffle avoidance and memory settings matter. I passed and would advise studying Spark internals, EMR configuration options and Glue job profiling to handle those tricky trade-off questions.

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Olga Kuznetsov

17 days ago

What surprised me most was how deep the processing questions went, especially around EMR tuning and Spark behavior under different workloads. I passed after doing hands on labs that made the tradeoffs around partitions, shuffle, and cost feel real.

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Aiko Lim

24 days ago

Storage questions often framed a performance versus cost trade-off and required choosing between S3, Redshift, and DynamoDB with the right partitioning strategy. Review S3 storage classes and lifecycle, Redshift distribution and sort keys, columnar compression, and DynamoDB hot key mitigation understanding access patterns helped me pass the exam.

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Emma Evans

27 days ago

Storage questions often framed cost versus performance trade offs, for example choosing between S3 with Athena and a provisioned data warehouse for ad hoc versus predictable query loads. Know compression and columnar formats, partitioning strategies, lifecycle policies, and how those affect throughput and query performance mastering those helped me during the exam. I took the exam and passed after drilling practical storage scenarios.

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Priya Rao

1 month ago

Storage scenarios asked to weigh S3 storage classes, partitioning, file formats and Redshift versus EMR for both cost and query performance. I managed to pass the exam and thanks Pass4Success for providing good collection of exam questions for preparation in short time.

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David Davis

2 months ago

The BDS-C00 exam leaned heavily on picking the right service for ingestion and storage, so I spent extra time comparing Kinesis, SQS, and Kafka options and it paid off. I passed by drilling scenario questions that forced me to justify each architecture choice.

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Gaurav Iyer

2 months ago

Processing had the trickiest scenario questions for me where you had to pick the right streaming architecture and tune Spark jobs for throughput and cost. Study Spark execution plans, EMR sizing, and Kinesis versus Firehose tradeoffs plus event time versus processing time windows I passed and thanks Pass4Success for a concise question bank that got me review-ready fast.

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Takashi Kim

2 months ago

Collection was brutal in the real exam with scenario questions asking which ingestion pattern to pick when you have bursty telemetry, strict ordering needs, or limited downstream throughput. Focus on how Kinesis, Firehose, and S3 intake differ, the effects of partition keys and buffering, and common formats like Avro and Parquet. I passed the test and the curated practice sets from Pass4Success helped me consolidate those trade offs quickly.

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Collection Thomas

2 months ago

The exam included scenario questions asking whether to use streaming ingestion or batch loads for different latency and ordering requirements, often comparing Kinesis, Firehose and S3 patterns. Focus on throughput, ordering guarantees, retry semantics and schema evolution I passed and appreciated Pass4Success for a concise question set that accelerated my prep.

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Data Security Martinez

18 days ago

Case studies tested encryption at rest and in transit, IAM least-privilege design, and how to implement envelope encryption with KMS while maintaining auditability. Review KMS key policies, cross-account access patterns, and logging/audit strategies since someone I know passed after tightening their knowledge of these controls.

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Storage Jackson

1 month ago

There were multi-step problems about designing a cost-efficient data lake, where you had to pick file formats and partitioning schemes to minimize scan costs. Study Parquet/ORC, partition pruning, compaction strategies and lifecycle policies since a friend passed after drilling these storage trade-offs.

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Processing Jackson

2 months ago

Several items probed subtle distinctions between batch ETL and real-time processing, including exactly-once semantics, stateful windowing and checkpointing mechanics. Make sure you understand Spark shuffle, Glue job bookmarking and streaming window types I managed to pass once I mastered those operational details.

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Analysis Anderson

24 days ago

Questions often presented query optimization scenarios in Redshift or Athena that required choosing distribution and sort keys or rewriting queries to reduce scanned data. Practice reading query plans, predicate pushdown and materialized views because a colleague passed after focusing on those analysis optimizations.

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Fatima Farooqi

2 months ago

Collection questions focused on choosing the right ingestion service when latency, ordering and throughput constraints conflict. I passed BDS-C00 and found hands-on practice with Kinesis Data Streams, Firehose, SQS and Snowball and a clear grasp of quotas made the scenario-based items much easier.

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Free Amazon BDS-C00 Exam Actual Questions

Note: Premium Questions for BDS-C00 were last updated On 19-08-2026 (see below)

Question #1

A company hosts a portfolio of e-commerce websites across the Oregon, N.Virginia, Ireland and Sydney AWS regions. Each site keeps log files that captures user behavior. The company has built an application that generates batches of product recommendations with collaborative filtering in Oregon. Oregon was selected because the flagship site is hosted there and provides the largest collection of data to train machine learning models against. The other regions do NOT have enough historic data to train accurate machine learning models.

Which set of data processing steps improves recommendations for each region?

AUse the e-commerce application in Oregon to write replica log files in each other region

BUse Amazon S3 bucket replication to consolidate log entries and builds a single model in
Oregon

CUse Kinesis as a butler for web logs and replicate logs to the Kinesis streams of a neighboring region

DUse the CloudWatch Logs agent to consolidate logs into a single CloudWatch logs group

Reveal Solution Hide Solution

Correct Answer: D

https://cloudacademy.com/blog/centralized-log-management-with-aws-cloudwatch-part-1-of-3/

Question #2

You have been tasked with deployment a solution for your company that will store images, which the marketing department will use for its campaigns. Employees are able to upload images via a web interface, and once uploaded, each image must be resized and watermarked with the company logo. Image resize and watermark is not time-sensitive and can be completed days after upload if required.

How should you design this solution in the most highly available and cost-effective way?

AConfigure your web application to upload images to the Amazon Elastic Transcoder service. Use the Amazon Elastic Transcoder watermark feature to add the company logo as a watermark on your images and then upload the final image into an Amazon s3 bucket

BConfigure your web application to upload images to Amazon S3, and send the Amazon S3 bucket URI to an Amazon SQS queue. Create an Auto Scaling group and configure it to use Spot instances, specifying a price you are willing to pay. Configure the instances in this Auto Scaling group to poll the SQS queue for new images and then resize and watermark the image before uploading the final images into Amazon S3

CConfigure your web application to upload images to Amazon S3, and send the S3 object URI to an Amazon SQS queue. Create an Auto Scaling launch configuration that uses Spot instances, specifying a price you are willing to pay. Configure the instances in this Auto Scaling group to poll the Amazon SQS queue for new images and then resize and watermark the image before uploading the new images into Amazon S3 and deleting the message from the Amazon SQS queue

DConfigure your web application to upload images to the local storage of the web server. Create a cronjob to execute a script daily that scans this directory for new files and then uses the Amazon EC2 Service API to launch 10 new Amazon EC2 instances, which will resize and watermark the images daily

Reveal Solution Hide Solution

Correct Answer: C

Question #3

You have an application running on an Amazon Elastic Compute Cloud instance, that uploads 5 GB video objects to Amazon Simple Storage Service (S3). Video uploads are taking longer than expected, resulting in poor application performance. Which method will help improve performance of your application?

AEnable enhanced networking

BUse Amazon S3 multipart upload

CLeveraging Amazon CloudFront, use the HTTP POST method to reduce latency.

DUse Amazon Elastic Block Store Provisioned IOPs and use an Amazon EBS-optimized instance

Reveal Solution Hide Solution

Correct Answer: B

Question #4

You are designing a web application that stores static assets in an Amazon Simple Storage

Service (S3) bucket. You expect this bucket to immediately receive over 150 PUT requests per second. What should you do to ensure optimal performance?

AUse multi-part upload.

BAdd a random prefix to the key names.

CAmazon S3 will automatically manage performance at this scale.

DUse a predictable naming scheme, such as sequential numbers or date time sequences, in the key names

Reveal Solution Hide Solution

Correct Answer: B

Question #5

A company receives data sets coming from external providers on Amazon S3. Data sets from different providers are dependent on one another. Data sets will drive at different and is no particular order.

A data architect needs to design a solution that enables the company to do the following:

* Rapidly perform cross data set analysis as soon as the data becomes available

* Manage dependencies between data sets that arrives at different times

Which architecture strategy offers a scalable and cost-effective solution that meets these requirements?

AMaintain data dependency information in Amazon RDS for MySQL. Use an AWS Pipeline job to load an Amazon EMR Hive Table based on task dependencies and event notification triggers in Amazon S3

BMaintain data dependency information in an Amazon DynamoDB table. Use Amazon SNS and event notification to publish data to a fleet of Amazon EC2 workers. Once the task dependencies have been resolved process the data with Amazon EMR

CMaintain data dependency information in an Amazon ElasticCache Redis cluster. Use Amazon S3 event notifications to trigger an AWS Lambda function that maps the S3 object to Redis. Once the dependencies have been resolved process the data with Amazon EMR

DMaintain data dependency information in an Amazon DynamoDB table. Use Amazon S3 event notifications to trigger an AWS Lambda function that maps the S3 object to the task associated with it in DynamoDB. Once all task dependencies have been resolved process the data with Amazon EMR

Reveal Solution Hide Solution

Correct Answer: C

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