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What is the AWS Certified Big Data Specialty exam?

AWS Certified Big Data Specialty exam validates the candidates expertise and technical knowledge in designing and implementing AWS services to derive from data. The candidate should have the ability to work on designing and maintaining Big Data. 

AWS Certified Big Data – Specialty is intended for individuals who perform complex Big Data analyses with at least 2 years of experience using AWS technology.The questions asked in this exam will be based on real time scenarios and you will require in depth knowledge on AWS Big Data technologies.

Abilities Validated by the Certification

Implement core AWS Big Data services according to basic architecture best practices

Design and maintain Big Data
Leverage tools to automate data analysis

Recommended Knowledge

We recommend candidates hold an AWS Certified Cloud Practitioner or a current Associate-level certification: AWS Certified Solutions Architect - Associate, AWS Certified Developer - Associate or AWS Certified SysOps Administrator - Associate
Background in defining and architecting AWS Big Data services with the ability to explain how they fit in the data life cycle of collection, ingestion, storage, processing, and visualization
Minimum five years hands-on experience in a data analytics field
Experience in designing a scalable and cost-effective architecture to process data

Share AWS Certified Big Data-Specialty exam questions and answers:

QUESTION 1 
A data engineer in a manufacturing company is designing a data processing platform that receives a large volume of unstructured data. The data engineer must populate a well-structured star schema in Amazon Redshift. What is the most efficient architecture strategy for this purpose?
A. Transform the unstructured data using Amazon EMR and generate CSV data. COPY the CSV data into the analysis schema within Redshift. 
B. Load the unstructured data into Redshift, and use string parsing functions to extract structured data for inserting into the analysis schema. 
C. When the data is saved to Amazon S3, use S3 Event Notifications and AWS Lambda to transform the file contents. Insert the data into the analysis schema on Redshift. 
D. Normalize the data using an AWS Marketplace ETL tool, persist the results to Amazon S3, and use AWS Lambda to INSERT the data into Redshift.
Answer: A 

QUESTION 2
A new algorithm has been written in Python to identify SPAM e-mails. The algorithm analyzes the free text contained within a sample set of 1 million e-mails stored on Amazon S3. The algorithm must be scaled across a production dataset of 5 PB, which also resides in Amazon S3 storage. Which AWS service strategy is best for this use case?
A. Copy the data into Amazon ElastiCache to perform text analysis on the in-memory data and export the results of the model into Amazon Machine Learning. 
B. Use Amazon EMR to parallelize the text analysis tasks across the cluster using a streaming program step. 
C. Use Amazon Elasticsearch Service to store the text and then use the Python Elasticsearch Client to run analysis against the text index. 
D. Initiate a Python job from AWS Data Pipeline to run directly against the Amazon S3 text files.
Answer: C 

QUESTION 3 
A data engineer chooses Amazon DynamoDB as a data store for a regulated application. This application must be submitted to regulators for review. The data engineer needs to provide a control framework that lists the security controls from the process to follow to add new users down to the physical controls of the data center, including items like security guards and cameras. How should this control mapping be achieved using AWS?
A. Request AWS third-party audit reports and/or the AWS quality addendum and map the AWS responsibilities to the controls that must be provided. 
B. Request data center Temporary Auditor access to an AWS data center to verify the control mapping. 
C. Request relevant SLAs and security guidelines for Amazon DynamoDB and define these guidelines within the application’s architecture to map to the control framework. 
D. Request Amazon DynamoDB system architecture designs to determine how to map the AWS responsibilities to the control that must be provided.
Answer: A 

QUESTION 4 
An administrator needs to design a distribution strategy for a star schema in a Redshift cluster. The administrator needs to determine the optimal distribution style for the tables in the Redshift schema. In which three circumstances would choosing Key-based distribution be most appropriate? (Select three.)
A. When the administrator needs to optimize a large, slowly changing dimension table. 
B. When the administrator needs to reduce cross-node traffic. 
C. When the administrator needs to optimize the fact table for parity with the number of slices. 
D. When the administrator needs to balance data distribution and collocation data. 
E. When the administrator needs to take advantage of data locality on a local node for joins and aggregates.
Answer: ACD 

QUESTION 5 
An administrator needs to design a strategy for the schema in a Redshift cluster. The administrator needs to determine the optimal distribution style for the tables in the Redshift schema.
In which two circumstances would choosing EVEN distribution be most appropriate? (Choose two.)
A. When the tables are highly denormalized and do NOT participate in frequent joins. 
B. When data must be grouped based on a specific key on a defined slice. 
C. When data transfer between nodes must be eliminated. 
D. When a new table has been loaded and it is unclear how it will be joined to dimension.
Answer: BD