________ is a technique in ETL that involves incrementally updating the data warehouse.
- Change Data Capture (CDC)
- Data Encryption
- Data Masking
- Data Normalization
Change Data Capture (CDC) is a technique in ETL (Extract, Transform, Load) that involves incrementally updating the data warehouse by identifying and capturing changes made to the source data since the last update. It is particularly useful for efficiently updating large datasets without reloading the entire dataset.
In a multinational corporation, how would a data warehouse facilitate the integration of different regional databases for global analysis?
- Data Fragmentation
- Data Replication
- Data Sharding
- ETL (Extract, Transform, Load) Processes
ETL processes are used to extract data from different regional databases, transform it into a common format, and load it into the data warehouse. This integration allows for global analysis and reporting across the entire organization.
Which algorithm is commonly used for classifying data into predefined categories?
- Decision Trees
- K-Means Clustering
- Linear Regression
- Principal Component Analysis
Decision Trees are commonly used for classifying data into predefined categories. They work by recursively splitting the data based on features, forming a tree structure that represents decision paths.
In dashboard design, _______ should be minimized to focus the viewer's attention on the most important data.
- Clutter
- Color
- Gridlines
- Labels
In dashboard design, clutter should be minimized to focus the viewer's attention on the most important data. Unnecessary elements, like excessive labels or gridlines, can distract from key insights.
_______ diagrams are effective for visualizing the structure of a dataset and the relationships between its components.
- Network
- Sankey
- Tree
- Venn
Network diagrams are effective for visualizing the structure of a dataset and the relationships between its components. Nodes represent data points, and edges represent connections or relationships, providing insights into the overall structure of the data.
Which method is commonly used to handle missing data in a dataset?
- Data normalization
- Mean imputation
- One-hot encoding
- Outlier detection
Mean imputation is a common method used to handle missing data. It involves replacing missing values with the mean of the observed values in that column, providing a simple way to fill in gaps without introducing bias.
For a company integrating data from multiple international sources, what ETL consideration is crucial for data consistency?
- Currency Conversion
- Data Quality Validation
- Language Translation
- Time Zone Standardization
Time zone standardization is crucial for ensuring data consistency when integrating data from multiple international sources. Consistent time representation is essential to avoid discrepancies and errors in data analysis and reporting.
Effective problem-solving often requires the ability to think _______ and consider various perspectives.
- Analytically
- Creatively
- Structurally
- Systematically
Effective problem-solving involves thinking systematically to consider various perspectives and analyze the problem from different angles. This helps in developing comprehensive and well-rounded solutions.
Which data structure is most efficient for implementing a priority queue?
- Binary Heap
- Linked List
- Queue
- Stack
A binary heap is the most efficient data structure for implementing a priority queue. It allows for efficient insertion and removal of the highest-priority element, making it a key choice for algorithms that require a priority queue, such as Dijkstra's algorithm.
When visualizing time-series data, which type of chart is typically most effective?
- Bar Chart
- Line Chart
- Pie Chart
- Scatter Plot
Line charts are most effective for visualizing time-series data. They show trends over time, making it easy to observe patterns, fluctuations, and overall changes in the data.