What is the primary purpose of an Entity-Relationship Diagram (ERD)?
- Describing entity attributes
- Identifying primary keys
- Representing data types
- Visualizing the relationships between entities
The primary purpose of an Entity-Relationship Diagram (ERD) is to visually represent the relationships between entities in a database model. This helps in understanding the structure and design of the database.
ETL tools often provide ______________ features to schedule, monitor, and manage the ETL workflows.
- Data aggregation
- Data modeling
- Data visualization
- Workflow orchestration
Workflow orchestration features in ETL tools enable users to schedule, monitor, and manage the execution of ETL workflows, ensuring efficient data movement and processing throughout the entire data pipeline.
Which data types are commonly stored in Data Lakes?
- Character, Date, Time, Array
- Integer, String, Float, Boolean
- Structured, Semi-structured, Unstructured, Binary
- Text, Numeric, Date, Boolean
Data Lakes commonly store structured, semi-structured, unstructured, and binary data types. This flexibility allows organizations to store and analyze various forms of data without the need for predefined schemas.
How does data profiling contribute to the effectiveness of the ETL process?
- Accelerating data processing, Simplifying data querying, Streamlining data transformation, Automating data extraction
- Enhancing data visualization, Improving data modeling, Facilitating data governance, Securing data access
- Identifying data anomalies, Ensuring data accuracy, Optimizing data storage, Validating data integrity
- Standardizing data formats, Enforcing data encryption, Auditing data access, Maintaining data backups
Data profiling in the ETL process involves analyzing data to identify anomalies, ensuring accuracy, optimizing storage, and validating integrity, which enhances the effectiveness and reliability of subsequent ETL operations.
What is the primary purpose of error handling in data pipelines?
- Enhancing data visualization techniques
- Identifying and resolving data inconsistencies
- Optimizing data storage efficiency
- Preventing data loss and ensuring data reliability
Error handling in data pipelines primarily focuses on preventing data loss and ensuring data reliability. It involves mechanisms to detect, capture, and address errors that occur during data processing, transformation, and movement. By handling errors effectively, data pipelines maintain data integrity and consistency, ensuring that accurate data is available for downstream analysis and decision-making.
What is the difference between a unique index and a non-unique index?
- A non-unique index allows duplicate values in the indexed column(s)
- A non-unique index does not allow NULL values in the indexed column(s)
- A unique index allows NULL values in the indexed column(s)
- A unique index allows only unique values in the indexed column(s)
A unique index enforces uniqueness, ensuring that each indexed value is unique, while a non-unique index allows duplicate values to be stored. Understanding this difference is crucial for data integrity and query optimization.
________ is a technique used in Dimensional Modeling to handle changes to dimension attributes over time.
- Fast Updating Dimension (FUD)
- Quick Altering Dimension (QAD)
- Rapidly Changing Dimension (RCD)
- Slowly Changing Dimension (SCD)
Slowly Changing Dimension (SCD) is a technique used in Dimensional Modeling to handle changes to dimension attributes over time. It involves maintaining historical data to accurately reflect changes in dimension attributes.
________ is a NoSQL database that is optimized for high availability and partition tolerance, sacrificing consistency under certain circumstances.
- Cassandra
- MongoDB
- Neo4j
- Redis
Cassandra is a NoSQL database designed for high availability and partition tolerance in distributed environments. It follows the principles of the CAP theorem, prioritizing availability and partition tolerance over consistency in certain scenarios.
In an ERD, a ________ is a property or characteristic of an entity.
- Attribute
- Entity
- Key
- Relationship
An attribute in an ERD represents a property or characteristic of an entity. It describes the data that can be stored for each instance of the entity, contributing to the overall definition of the entity's structure.
What is a Slowly Changing Dimension (SCD) in Dimensional Modeling?
- A dimension that changes at a regular pace
- A dimension that changes frequently over time
- A dimension that changes unpredictably over time
- A dimension that rarely changes over time
A Slowly Changing Dimension (SCD) in Dimensional Modeling is a dimension that changes over time but not frequently. It typically records historical data, preserving the history of changes in the dimension.