_________ is a critical process in MDM for linking all data elements associated with a particular entity.
- Data Aggregation
- Data Deduplication
- Data Integration
- Data Linkage
Data Linkage is a critical process in Master Data Management (MDM) for linking all data elements associated with a particular entity. It involves establishing relationships between diverse data sources to create a unified and accurate view of master data.
In a binary search algorithm, what is the time complexity for searching an element in a sorted array of n elements?
- O(1)
- O(log n)
- O(n)
- O(n^2)
The time complexity of a binary search algorithm is O(log n), as it repeatedly divides the search interval in half, resulting in a logarithmic time complexity. This makes it more efficient than linear search algorithms (O(n)).
How does a NoSQL database differ from a traditional SQL database?
- NoSQL databases are limited to a single data model.
- NoSQL databases are schema-less, allowing for flexible and dynamic data models.
- SQL databases are only suitable for small-scale applications.
- SQL databases use a key-value pair storage mechanism.
NoSQL databases provide a flexible and dynamic data model, allowing for schema-less data storage. This contrasts with traditional SQL databases, which follow a structured, tabular format with a fixed schema.
For real-time data processing, ETL uses ________ to handle streaming data.
- Apache Kafka
- Hadoop
- MongoDB
- SQL Server
Apache Kafka is commonly used in ETL processes for real-time data processing. It is a distributed event streaming platform that excels at handling high-throughput, fault-tolerant, and scalable data streams, making it suitable for managing streaming data in ETL pipelines.
A _______ tree is a data structure that allows fast search, insert, delete, and nearest-neighbor operations.
- AVL
- B-Tree
- Heap
- Trie
A B-Tree is a self-balancing tree data structure that allows for efficient search, insert, delete, and nearest-neighbor operations. It is commonly used in databases and file systems for its balanced nature, ensuring consistent performance.
When you need to create a lagged feature in a time series dataset in Pandas, which function would you use?
- delay()
- diff()
- lag()
- shift()
The shift() function in Pandas is used to create lagged features in a time series dataset. It shifts the values of a column by a specified number of periods, allowing you to create lagged versions of the original data for time series analysis.
In time series analysis, how is the term 'stationarity' best described?
- The ability of a time series to move in a straight line
- The predictability of future values in a time series
- The presence of external factors affecting a time series
- The statistical properties of a time series remaining constant over time
Stationarity refers to the statistical properties of a time series remaining constant over time. Achieving stationarity is important for accurate modeling and forecasting in time series analysis.
When creating a financial forecast model in Excel, what techniques would be crucial for accurate predictions and data integrity?
- Auditing Tools
- Data Validation
- Scenario Manager
- Sensitivity Analysis
Scenario Manager in Excel is crucial for creating different scenarios in a financial forecast model, allowing for better analysis of potential outcomes. Sensitivity Analysis, Data Validation, and Auditing Tools are important for maintaining data integrity and accuracy in financial models.
Which metric is commonly used to evaluate the accuracy of a predictive model in classification tasks?
- Accuracy
- Mean Squared Error
- Precision
- R-squared
Accuracy is a common metric used to evaluate the performance of a predictive model in classification tasks. It represents the ratio of correctly predicted instances to the total instances and provides a general measure of the model's correctness. Other metrics, such as precision, recall, and F1 score, are also used depending on the specific requirements of the task.
When using Pandas, how do you check the first five rows of a DataFrame?
- head(5)
- first(5)
- top(5)
- show(5)
To check the first five rows of a DataFrame in Pandas, you use the head(5) method. This function returns the first N rows of the DataFrame, and it is a common practice to use head() with the argument 5 to display the initial rows. The other options are not valid methods for achieving this task in Pandas.