In Tableau, _________ is a unique feature that enables interactive data exploration through natural language queries.
- Ask Data
- Quick Insights
- Smart Analytics
- Tableau Explorer
Ask Data is a unique feature in Tableau that enables users to interactively explore and analyze data using natural language queries. This feature allows for a more intuitive and user-friendly approach to data exploration. Quick Insights and Smart Analytics are not specific features for natural language queries, and Tableau Explorer is a user role, not a feature.
What advanced feature in BI tools helps in forecasting future trends based on historical data?
- Clustering
- Data Mining
- Predictive Analytics
- Text Analysis
Predictive Analytics is the advanced feature in BI tools that involves using historical data to identify trends and make predictions about future outcomes. It is a valuable tool for making data-driven decisions.
In a script, numbers = [1, 2, 3]; new_numbers = [x * 10 for x in numbers]; print(new_numbers) is executed. What is the output?
- [1, 1, 2, 2, 3, 3]
- [1, 10, 2, 20, 3, 30]
- [1, 2, 3, 1, 2, 3, 1, 2, 3]
- [10, 20, 30]
The output is a list comprehension that multiplies each element in numbers by 10. Therefore, the result is [10, 20, 30].
In the context of data warehousing, what is a 'dimension' typically used for?
- Describing the who, what, where aspects of business
- Managing transactions
- Organizing data alphabetically
- Storing historical data
A 'dimension' in data warehousing is typically used for describing the various aspects of business, such as who, what, where, and when. It provides context and categorizes data, aiding in meaningful analysis and reporting.
What is the output of print("Hello, World!"[7]) in Python?
- W
- l
- o
- r
Python uses zero-based indexing, so indexing at 7 gives the second 'o' in the string "Hello, World!".
What is the primary challenge in dealing with 'dirty data' in big data applications?
- Data Privacy Concerns
- Inconsistent Data
- Lack of Processing Power
- Volume of Data
The primary challenge in dealing with 'dirty data' is the inconsistency in the data, including missing values, inaccuracies, and variations in formats, which can adversely affect analysis and decision-making.
In a DBMS, _______ refers to the ability to restore the database to a specific point in time.
- Data Archiving
- Data Clustering
- Database Indexing
- Point-in-Time Recovery
Point-in-Time Recovery is a feature in a DBMS that allows the restoration of a database to a specific point in time, providing a way to recover data up to a particular moment. Data Archiving, Database Indexing, and Data Clustering are database-related concepts but do not specifically refer to the ability to restore to a particular point in time.
What data structure would be most efficient for implementing a non-binary tree with multiple children per node?
- Graph
- Heap
- Queue
- Trie
A non-binary tree with multiple children per node is best represented as a graph. Graphs are versatile data structures that can model relationships between nodes with arbitrary connections, making them suitable for various scenarios, including non-binary trees.
When would you use a pie chart in data visualization?
- Comparing individual categories to the whole
- Displaying trends over time
- Highlighting relationships between two variables
- Showing the distribution of a single variable
A pie chart is useful when you want to show the proportion of individual categories in relation to the whole. It is effective for displaying the distribution of a dataset's components.
Data _______ involves correcting wrong or inconsistent parts of the data.
- Augmentation
- Cleansing
- Transformation
- Validation
Data cleansing is the process of identifying and correcting errors or inconsistencies in the dataset. It ensures that the data is accurate and reliable for analysis. Data augmentation, validation, and transformation are different aspects of data preprocessing.