AWS Data Engineer Associate Test - 2

Welcome to your AWS Data Engineer Associate – Test-02

Name

Phone

Q1. When considering schema evolution in data models, which technique ensures backward and forward compatibility, allowing for changes without affecting existing data?

Select 1 option(s):

Schema normalization

Schema deprecation

Schema duplication

Schema versioning

Q2. When implementing data cleansing techniques, what aspects must be considered to ensure data integrity and accuracy? (Select all that apply)

Select 2 option(s):

Handling missing or inconsistent data values

Retaining redundant data for future analysis

Ensuring data transformations retain original data context

Adhering to data retention policies

Q3. How does schema evolution impact the maintenance and management of data models over time in evolving systems?

Select 1 option(s):

Schema evolution ensures static data models without adaptation to changing requirements.

Schema evolution accommodates changes in data structures, ensuring compatibility and adaptation to evolving needs.

Schema evolution simplifies data integration but introduces data inconsistencies.

Schema evolution limits data access to specific user roles.

Q4. Which characteristics differentiate serverless data processing from traditional data processing architectures?

Select 1 option(s):

Serverless architectures require manual resource provisioning.

Serverless architectures rely on constant infrastructure maintenance.

Serverless architectures scale automatically and charge based on actual usage.

Serverless architectures lack compatibility with cloud services.

Q5. Which AWS service offers the capability to define, manage, and orchestrate AWS resources as code?

Select 1 option(s):

AWS Elastic Beanstalk

AWS OpsWorks

AWS Amplify

AWS CloudFormation

Q6. How do indexing and partitioning strategies contribute to optimizing query performance in large-scale databases?

Select 1 option(s):

Indexing and partitioning enhance query performance by facilitating efficient data access and retrieval.

Indexing and partitioning increase data retrieval time significantly.

Indexing and partitioning are irrelevant in large-scale databases.

Indexing and partitioning reduce data redundancy but slow down query performance.

Q7. How do policy-based authorization mechanisms differ from tag-based and attribute-based authorization methods in AWS? (Select all that apply)

Select 2 option(s):

Select Attribute-based authorization utilizes data attributes for access control.1 option(s):

Policy-based authorization relies on predefined rules for access grants.

Policy-based authorization depends on user-defined tags for access control.

Tag-based authorization enforces access based on user-assigned attributes.

Q8. When optimizing SQL queries for large datasets, what technique is employed to limit the query‘s result set?

Select 1 option(s):

Data partitioning

Result set filtering

Subquery optimization

Data aggregation

Q9. What defines the concept of data masking and key salting in data security measures? (Select all that apply)

Select 2 option(s):

Data masking replaces sensitive information with fictitious or scrambled data.

Data masking involves encrypting sensitive information for secure storage.

Key salting ensures encryption without affecting data readability.

Key salting enhances encryption by adding random data to encryption keys.

Q10. Which AWS service is specifically designed to automate the configuration, management, and scaling of a distributed computing infrastructure?

Select 1 option(s):

Amazon EMR

Amazon S3

Amazon Redshift

AWS Glue

Q11. When considering stateful data transactions, what characteristic distinguishes them from stateless transactions?

Select 1 option(s):

Stateful transactions are not scalable in distributed systems.

Stateful transactions maintain information between interactions.

Stateful transactions lack data consistency across multiple operations.

Stateless transactions only handle real-time data processing.

Q12. How does the choice of data serialization formats impact data ingestion and processing in distributed computing systems?

Select 1 option(s):

Serialization formats influence only batch data processing.

Serialization formats are applicable only in stateful transactions.

Serialization formats have no impact on distributed systems.

Serialization formats affect data transfer efficiency and compatibility in distributed systems.

Q13. What role does metadata play in efficient data cataloging and organization? (Select all that apply)

Select 2 option(s):

Metadata provides security encryption keys for data storage.

Metadata assists in tracking data lineage and version control for data sets.

Metadata controls data access permissions for users.

Metadata includes data descriptions, aiding in data management and organization.

Q14. In the context of schema evolution, which technique ensures the least disruption while implementing changes in data models?

Select 1 option(s):

Schema versioning

Schema normalization

Schema deprecation

Schema duplication

Q15. How do different data storage formats impact data querying and processing in distributed databases? (Select all that apply)

Select 2 option(s):

ORC enhances parallel processing capabilities in distributed databases.

Parquet facilitates columnar storage for improved querying performance.

CSV offers faster querying than Parquet in distributed systems.

JSON enables efficient compression techniques for large-scale databases.

Q16. When working with stateful data transactions, what defines the persistence of the transactional state?

Select 1 option(s):

Persistence depends on network connectivity.

Persistence is irrelevant in stateful transactions.

Persistence maintains the state beyond individual transactions.

Persistence lasts only during the transaction‘s execution.

Q17. How does data classification assist in efficient organization and management within a data cataloging system? (Select all that apply)

Select 1 option(s):

Data classification ensures data normalization.

Data classification controls data access permissions.

Data classification categorizes data based on attributes and characteristics.

Data classification facilitates data encryption.

Q18. What practices are involved in centralizing AWS logs for comprehensive visibility and analysis? (Select all that apply)

Select 2 option(s):

Aggregating logs from multiple AWS services into a single AWS S3 bucket

Utilizing AWS CloudTrail for monitoring access to AWS services

Using AWS Athena for live log analysis across services

Integrating AWS Inspector to consolidate logs for analysis

Q19. How do scripting capabilities contribute to maintaining and troubleshooting data processing in AWS services?

Select 1 option(s):

Scripting enables efficient data encryption techniques.

Scripting allows customization and automation of data processing workflows.

Scripting automates data visualization processes.

Scripting improves data compression algorithms.

Q20. What encryption options are commonly available in AWS analytics services like Amazon Redshift and AWS EMR? (Select all that apply)

Select 2 option(s):

Client-side encryption

Encryption at rest

In-transit encryption

Server-side encryption

Q21. How do archiving strategies contribute to optimizing storage costs and data availability? (Select all that apply)

Select 1 option(s):

Archiving strategies prioritize high-speed access to archived data.

Archiving strategies duplicate data for high availability.

Archiving strategies move infrequently accessed data to lower-cost storage tiers while maintaining accessibility.

Archiving strategies focus on immediate data deletion for cost savings.

Q22. When considering the scalability of ETL pipelines, which factor significantly influences their ability to handle increasing data volumes?

Select 1 option(s):

Schema flexibility

Error handling mechanisms

Parallel processing capabilities

Compression algorithms

Q23. In the context of ETL pipelines, what role do buffer systems play during data transformation?

Select 1 option(s):

Buffers solely handle data encryption.

Buffers are irrelevant in ETL pipelines.

Buffers manage real-time data ingestion.

Buffers temporarily store data to optimize processing efficiency.

Q24. In data transformation processes, what is the primary role of data enrichment?

Select 1 option(s):

Data enrichment enhances data quality by adding additional context or information.

Data enrichment simplifies data storage procedures.

Data enrichment focuses on optimizing data compression techniques.

Data enrichment is irrelevant in ETL pipelines.

Q25. How does policy-based authorization in AWS differ from role-based authorization and attribute-based authorization? (Select all that apply)

Select 2 option(s):

Policy-based authorization allows unrestricted access across all AWS services.

Attribute-based authorization restricts access based on data attributes.

Policy-based authorization relies on predefined rules or policies.

Role-based authorization depends on user-defined roles for access control.

Q26. When configuring batch data ingestion, which factor significantly impacts the reliability of the process?

Select 1 option(s):

Network bandwidth availability

Data schema flexibility

Data compression techniques

Error handling mechanisms

Q27. When designing ETL pipelines, which AWS service facilitates the execution of tasks in response to events triggered by changes in AWS resources?

Select 1 option(s):

AWS Glue

AWS Lambda

Amazon Kinesis Data Firehose

AWS Step Functions

Q28. What role does data retention policy play in managing the lifecycle of data in a storage solution?

Select 1 option(s):

Data retention policy influences data encryption techniques.

Data retention policy dictates data archival strategies.

Data retention policy ensures consistent data duplication.

Data retention policy automates data transformation.

Q29. How do indexing and partitioning strategies enhance query performance in distributed databases?

Select 1 option(s):

Indexing increases data redundancy, slowing down query performance.

Indexing and partitioning are ineffective in distributed databases.

Indexing and partitioning facilitate efficient data access and retrieval.

Partitioning reduces data retrieval speed significantly.

Q30. What measures contribute to differentiating AWS managed policies from customer managed policies in AWS IAM? (Select all that apply)

Select 2 option(s):

Customer managed policies are customizable by AWS users.

AWS managed policies allow direct assignment to IAM users.

Customer managed policies are customized by AWS and can‘t be altered.

AWS managed policies are predefined and can‘t be modified.

Q31. When applying API calls for data processing in AWS services, what functions do these calls primarily serve? (Select all that apply)

Select 1 option(s):

Orchestrating provisioning of compute resources

Managing and controlling data access permissions

Enabling secure data transfer across servers

Automating interactions and data manipulation within AWS services

Q32. Which storage solutions are suitable for addressing hot and cold data requirements in terms of cost-effectiveness and performance? (Select all that apply)

Select 2 option(s):

Amazon S3 Glacier

Amazon EBS

Amazon DynamoDB

Amazon RDS

Q33. What factors contribute to effective data aggregation in analytics? (Select all that apply)

Select 2 option(s):

Aggregation facilitates data normalization techniques.

Aggregation enables parallel processing of data.

Aggregation summarizes and condenses data for easier analysis.

Aggregation methods enhance data storage efficiency.

Q34. How does Amazon Macie ensure compliance and data quality in data operations and support?

Select 1 option(s):

Amazon Macie identifies data skew for balancing data distribution.

Amazon Macie performs automated data sampling for quality assessment.

Amazon Macie analyzes data access patterns for security and compliance.

Amazon Macie validates data completeness and accuracy.

Q35. How does the principle of least privilege influence authorization practices in AWS security?

Select 1 option(s):

Least privilege restricts access to only the necessary resources for specific tasks.

Least privilege grants extensive access to streamline operations.

Least privilege ensures minimal access for all users within an AWS environment.

Least privilege permits unrestricted access to all AWS services.

Q36. How does the choice between synchronous and asynchronous data replication methods influence data consistency and availability in storage systems?

Select 1 option(s):

Asynchronous replication offers immediate data availability without affecting consistency.

Asynchronous replication guarantees immediate consistency but compromises data availability.

Synchronous replication introduces significant delays in data availability.

Synchronous replication ensures high availability but may impact data consistency during network disruptions.

Q37. How do data storage formats such as Parquet and ORC contribute to optimizing data storage and query performance in analytical databases?

Select 1 option(s):

Parquet and ORC formats limit query capabilities.

Parquet and ORC formats support efficient data compression and columnar storage.

Parquet and ORC formats introduce data redundancy.

Parquet and ORC formats focus on real-time data processing.

Q38. In the context of data transformation in ETL pipelines, what role does AWS Step Functions serve?

Select 1 option(s):

AWS Step Functions orchestrates serverless functions for data transformation.

AWS Step Functions manage data access permissions.

AWS Step Functions are unrelated to data transformation in ETL pipelines.

AWS Step Functions solely handles data storage and retrieval.

Q39. Which factors significantly impact the efficiency of ETL pipelines when dealing with high volumes of varied data?

Select 1 option(s):

Data schema complexity and data lineage

Data compression techniques and encryption algorithms

Hardware specifications and CPU utilization

Network bandwidth and storage capacity

Q40. Which SQL query optimization technique involves restructuring the query to minimize resource consumption and improve efficiency?

Select 1 option(s):

Query caching

Query normalization

Query optimization

Query parallelization

Q41. How does data access logging contribute to audit preparation and security in AWS environments?

Select 2 option(s):

Data access logs serve as immutable records for compliance audits.

Data access logs identify potential weaknesses in encryption protocols.

Data access logs are useful for real-time threat detection.

Data access logs automate security updates and patches.

Q42. Which authentication methods align with the principle of role-based access control (RBAC) for AWS services? (Select all that apply)

Select 3 option(s):

Token-based authentication

Password-based authentication

Certificate-based authentication

Role-based authentication

Q43. What practices can ensure centralized AWS logs for comprehensive visibility and analysis? (Select all that apply)

Select 2 option(s):

Integrating AWS Inspector to consolidate logs for analysis

Using AWS Athena for real-time log analysis across services

Directing logs from multiple AWS services to a single AWS S3 bucket

Employing AWS CloudTrail for monitoring access to AWS services

Q44. What distinguishes the data ingestion of structured data from unstructured data in terms of ETL pipeline processing?

Select 1 option(s):

Unstructured data ingestion does not involve transformation steps.

Structured data ingestion necessitates predefined schemas.

Structured data ingestion requires more complex transformation processes.

Unstructured data ingestion involves fewer security considerations.

Q45. What role does data classification play in organizing and managing data in a cataloging system?

Select 1 option(s):

Data classification limits data access for users.

Data classification focuses on data encryption standards.

Data classification ensures data integrity by preventing data duplication.

Data classification categorizes and tags data based on attributes and characteristics for efficient organization and management.

Q46. How do JOIN clauses impact the complexity and performance of SQL queries in data analysis? (Select all that apply)

Select 2 option(s):

JOIN clauses restrict data access within SQL queries.

JOIN clauses simplify query optimization in SQL.

JOIN clauses combine data from multiple tables for complex analysis.

JOIN clauses may introduce computational overhead in queries.

Q47. Which components constitute a data catalog in an enterprise environment? (Select all that apply)

Select 2 option(s):

Data migration tools

Data source locations and metadata

Data descriptions and attributes

Data encryption keys

Q48. In a data engineering context, how does schema-on-read differ from schema-on-write approaches?

Select 1 option(s):

Schema-on-write validates data integrity during ingestion.

Schema-on-read emphasizes data validation during ingestion.

Schema-on-read requires predefined data structures before ingestion.

Schema-on-write allows flexibility in data storage without predefined structures.

Q49. How does AWS Lambda contribute to data processing within ETL pipelines?

Select 1 option(s):

AWS Lambda only supports structured data processing.

AWS Lambda exclusively handles batch processing tasks.

AWS Lambda primarily focuses on data storage.

AWS Lambda executes code in response to events without managing infrastructure.

Q50. When employing Continuous Integration and Continuous Delivery (CI/CD) for data pipelines, how does version control contribute to the development process?

Select 1 option(s):

Version control is only applicable to structured data processing.

Version control tracks changes, facilitates collaboration, and ensures pipeline stability.

Version control ensures data security in pipelines.

Version control is irrelevant in CI/CD practices.

Q51. When determining the appropriate storage solution aligned with data migration requirements, what aspects are crucial for compatibility and seamless data transfer? (Select all that apply)

Select 2 option(s):

Network latency and throughput

Data storage formats

Storage service durability

Data replication mechanisms

Q52. How does the application of rolling averages contribute to data analysis and forecasting?

Select 2 option(s):

Rolling averages are ineffective in data analysis.

Rolling averages facilitate trend identification in time-series data.

Rolling averages improve data visualization for non-sequential data.

Rolling averages smooth out fluctuations and noise in data.

Q53. How does distributed computing enhance the scalability of data processing systems?

Select 1 option(s):

By prioritizing sequential data processing

By concentrating processing power within a single server

By allowing parallel processing across multiple nodes

By limiting data access to specific regions

Q54. What is the role of Amazon CloudWatch in maintaining and monitoring data pipelines?

Select 1 option(s):

Amazon CloudWatch provides data encryption for secure pipeline operations.

Amazon CloudWatch controls data access permissions within pipelines.

Amazon CloudWatch automates data transformation processes in pipelines.

Amazon CloudWatch monitors application performance metrics for pipeline optimization.

Q55. In data lifecycle management, what purpose do archiving strategies serve in optimizing storage costs and data accessibility?

Select 1 option(s):

Archiving strategies duplicate data for high availability.

Archiving strategies move infrequently accessed data to lower-cost storage tiers while maintaining accessibility.

Archiving strategies prioritize high-speed access to archived data.

Archiving strategies focus on immediate data deletion to reduce storage costs.

Q56. When managing the lifecycle of data, what role do data retention policies play in compliance and storage optimization?

Select 1 option(s):

Data retention policies solely focus on data encryption standards.

Data retention policies help meet legal requirements and optimize storage costs.

Data retention policies restrict data access for users.

Data retention policies ensure long-term storage without considering access patterns.

Q57. When designing data models for structured, semi-structured, and unstructured data, what consideration is crucial for ensuring accurate data representation?

Select 1 option(s):

Data partitioning

Data redundancy

Data normalization

Data serialization

Q58. When considering SQL query optimization, what impact does indexing have on query performance?

Select 1 option(s):

Indexing improves query performance by reducing data access overhead.

Indexing slows down query performance due to increased data retrieval.

Indexing is irrelevant to query optimization in SQL.

Indexing applies only to unstructured data sources.

Q59. Which AWS service facilitates the real-time processing of streaming data with low latency and high durability?

Select 1 option(s):

AWS Glue

Amazon Kinesis Data Streams

AWS Data Pipeline

AWS Lambda

Q60. What measures can be employed to ensure compliance with data privacy regulations regarding Personally Identifiable Information (PII) in AWS environments? (Select all that apply)

Select 3 option(s):

Applying data anonymization techniques to PII

Utilizing geographically distributed data storage for PII

Defining role-based access controls for PII

Implementing data encryption at rest and in transit