Which metric is commonly monitored to ensure data pipeline reliability?

  • Data freshness
  • Data latency
  • Data throughput
  • Data volume
Data latency is a crucial metric monitored to ensure data pipeline reliability. It measures the time taken for data to travel from the source to the destination, indicating the efficiency and responsiveness of the pipeline. Monitoring data latency helps detect delays and bottlenecks, enabling timely optimizations to maintain pipeline reliability and meet service-level agreements (SLAs).

A ________ index includes additional columns beyond those in the index key, allowing queries to be answered directly from the index without having to access the table data.

  • Clustered
  • Composite
  • Non-clustered
  • Unique
A composite index includes additional columns beyond those in the index key, allowing queries to retrieve necessary data directly from the index without accessing the table data, enhancing query performance.

What is the primary purpose of ETL optimization techniques?

  • Boosting data processing speed
  • Enhancing data quality
  • Improving data security
  • Increasing data storage capacity
ETL optimization techniques primarily focus on boosting data processing speed. This involves refining the Extract, Transform, and Load (ETL) processes to make them more efficient, reducing overall execution time.

What considerations should be made when selecting between different data modeling tools such as ERWin and Visio for a specific project?

  • Data volume, Data velocity, Data variety, Data veracity
  • Development methodology, Project timeline, Stakeholder requirements, Budget
  • Feature set, Compatibility with existing systems, Cost, Support and documentation
  • Performance, Scalability, Security, User interface
When selecting between data modeling tools like ERWin and Visio, considerations should include evaluating their feature set, compatibility with existing systems, cost, and the availability of support and documentation to meet the project's requirements effectively.

In Dimensional Modeling, what are Dimensions?

  • Categories that provide context to the facts
  • Primary keys in a relational database
  • Tables that store descriptive attributes
  • Tables that store transactional data
Dimensions in Dimensional Modeling are categories or entities that provide context to the facts stored in the Fact Table. They contain descriptive attributes that help in analyzing and understanding the data.

Which type of data model represents the high-level structure and relationships between data entities and is independent of any specific database management system?

  • Conceptual Data Model
  • Hierarchical Data Model
  • Logical Data Model
  • Physical Data Model
A conceptual data model represents the high-level structure and relationships between data entities. It is independent of any specific database management system and focuses on the business concepts and rules.

In an RDBMS, a ________ is a virtual table that represents the result of a database query.

  • Index
  • Stored Procedure
  • Trigger
  • View
In an RDBMS, a view is a virtual table that represents the result of a database query. It provides a way to present data in a structured manner without storing the actual data, thus simplifying data access and enhancing security.

Scenario: Your team is experiencing performance issues with a database application. As a data engineer, how would you leverage physical data modeling to address these issues?

  • Denormalization of database schema
  • Implementing additional constraints and checks
  • Normalization of database schema
  • Optimizing table indexes and partitioning
Leveraging physical data modeling involves optimizing table indexes, partitioning data appropriately, and organizing the physical layout of data to enhance performance and address specific performance issues in the database application.

Which data extraction technique involves querying a database directly to retrieve specific data sets?

  • Direct extraction
  • Full extraction
  • Incremental extraction
  • Parallel extraction
Direct extraction involves querying a database directly to retrieve specific data sets based on defined criteria. This method is often used when only a subset of data is required for analysis or processing.

Data modeling tools such as ERWin or Visio help in visualizing and designing ________.

  • Data Flow Diagrams (DFDs)
  • Entity-Relationship Diagrams (ERDs)
  • Flowcharts
  • UML diagrams
Data modeling tools like ERWin or Visio primarily aid in visualizing and designing Entity-Relationship Diagrams (ERDs), which depict the entities, attributes, and relationships in a database schema.

What is a broadcast variable in Apache Spark, and how is it used?

  • A variable cached in memory for faster access
  • A variable replicated to every executor node
  • A variable shared across all nodes in a cluster
  • A variable used for inter-process communication
A broadcast variable in Apache Spark is replicated to every executor node for efficient data distribution. It's used for broadcasting large read-only datasets to all tasks across the cluster to avoid excessive data shuffling.

How does Extraction-Transformation-Loading (ETL) differ from Extract-Load-Transform (ELT) in terms of data extraction?

  • Data is extracted from the target system back to the source system
  • Data is extracted in real-time from the source system
  • Data is loaded into the target system before transformation
  • Data is transformed before loading into the target system
ETL involves extracting data, then transforming it, and finally loading it into the target system, whereas ELT involves extracting data first, then loading it into the target system, and finally transforming it.