A retail company is implementing an ETL process for its online sales. They want to ensure that even if the ETL process fails mid-way, they can quickly recover without data inconsistency. Which strategy should they consider?
- Checkpoints and Logging
- Compression and Encryption
- Data Archiving
- Data Sharding
To ensure quick recovery without data inconsistency in case of an ETL process failure, the retail company should consider using checkpoints and logging. Checkpoints allow the process to save its progress at various stages, and logging records all activities and changes. In case of failure, the process can resume from the last successful checkpoint, minimizing data inconsistencies and potential data loss.
In the context of dashboards, what term is used to describe a graphical representation that provides at-a-glance views of key performance indicators (KPIs)?
- Gadgets
- Icons
- Tiles
- Widgets
In the context of dashboards, a "Tile" is used to describe a graphical representation that provides at-a-glance views of key performance indicators (KPIs). Tiles are often customizable components that display summarized data or metrics, making it easy for users to monitor and understand essential information.
What is the main advantage of distributing data across multiple storage devices or locations in a Distributed Data Warehousing setup?
- Enhanced data redundancy
- Improved data security
- Scalability and load balancing
- Simplified data management
The main advantage of distributing data across multiple storage devices or locations in a Distributed Data Warehousing setup is scalability and load balancing. It allows for the efficient distribution of data, ensuring that query workloads can be evenly spread across resources, thus optimizing performance and handling increased data volumes effectively.
In cloud environments, data redundancy and high availability are often achieved through _______ across multiple zones or regions.
- Data Elevation
- Data Isolation
- Data Mirroring
- Data Replication
In cloud environments, data redundancy and high availability are frequently accomplished through "Data Replication," which involves duplicating data across multiple zones or regions. This redundancy ensures that data remains accessible and intact, even in the event of hardware failures or other disruptions.
Which type of chart is most suitable for displaying the distribution of a single continuous dataset?
- Bar Chart
- Histogram
- Line Chart
- Pie Chart
A histogram is the most suitable chart for displaying the distribution of a single continuous dataset. It shows the frequency of data points in specific intervals, providing insights into the data's distribution and central tendencies. It's commonly used in statistics and data analysis.
Which type of Slowly Changing Dimension (SCD) uses a separate table to store both current and historical data for an attribute?
- SCD Type 1
- SCD Type 2
- SCD Type 3
- SCD Type 4
SCD Type 2 is the type of Slowly Changing Dimension that uses a separate table to store both the current and historical data for an attribute. It allows you to maintain a historical record of changes over time while preserving the current value in the main table. This is particularly useful in data warehousing for tracking changes to dimension attributes.
In a star schema, if a dimension table contains a hierarchy of attributes (like Year > Quarter > Month), but these attributes are not broken into separate tables, this design is contrary to which schema?
- Fact Constellation Schema
- Galaxy Schema
- Hierarchical Schema
- Snowflake Schema
In a star schema, dimension tables are typically denormalized, meaning that hierarchies of attributes are not broken into separate tables. This design is contrary to the snowflake schema, where attributes are often normalized into separate tables to reduce redundancy. In a snowflake schema, the Year, Quarter, and Month attributes might be split into separate tables, leading to more complex joins.
What does the "in-memory" aspect of a data warehouse mean?
- Data is stored in RAM for faster access
- Data is stored on cloud servers
- Data storage on external storage devices
- Storing data in random memory locations
The "in-memory" aspect of a data warehouse means that data is stored in random-access memory (RAM) for faster access and processing. Storing data in RAM allows for high-speed data retrieval and analytics, as data can be accessed more quickly compared to traditional storage on external devices like hard drives. This leads to improved query performance and faster data analysis.
Which term refers to the process of identifying and correcting (or removing) errors and inconsistencies in data?
- Data Aggregation
- Data Cleansing
- Data Profiling
- Data Transformation
The process of identifying and correcting (or removing) errors and inconsistencies in data is known as "Data Cleansing." Data cleansing involves detecting and resolving issues like missing values, duplicates, and inaccuracies, ensuring data quality and reliability.
What is the primary purpose of a Data Warehouse?
- Data Analysis
- Data Backup
- Data Entry
- Data Extraction
The primary purpose of a Data Warehouse is to facilitate data analysis. Data Warehouses consolidate and store data from various sources, making it available for in-depth analysis, reporting, and decision-making. It provides a centralized repository for historical and current data, enabling businesses to gain insights and make data-driven decisions.