Which type of data can often be represented as a combination of structured tables with metadata or annotations?
- Time Series Data
- Geospatial Data
- Semi-Structured Data
- Categorical Data
Semi-structured data is a type of data that falls between structured and unstructured data. It can often be represented as a combination of structured tables with additional metadata or annotations. This format provides some level of organization and makes it more manageable for analysis. Examples of semi-structured data include JSON, XML, and log files, which have some inherent structure but may also contain unstructured elements.
Real-time data processing is also commonly referred to as ________ processing.
- Batch Processing
- Stream Processing
- Offline Processing
- Parallel Processing
Real-time data processing is commonly referred to as "Stream Processing." In this approach, data is processed as it is generated, allowing for real-time analysis and decision-making. It is crucial in applications where immediate insights or actions are required.
Which data warehousing schema involves a central fact table and a set of dimension tables?
- Snowflake Schema
- Star Schema
- Denormalized Schema
- NoSQL Schema
The Star Schema is a common data warehousing schema where a central fact table stores quantitative data, and dimension tables provide context and details about the data. This schema simplifies querying and reporting.
You are working with a database that contains tables with customer details, purchase histories, and product information. However, there are also chunks of data that contain email communications with the customer. How would you categorize this database in terms of data type?
- Structured data
- Semi-structured data
- Unstructured data
- Big data
This database contains a mix of structured data (customer details, purchase histories, and product information) and semi-structured data (email communications). Semi-structured data is characterized by having some structure but also includes elements like emails, making it different from fully structured data.
The statistical test called _______ is used when we want to compare the means of more than two groups.
- T-test
- Chi-squared
- ANOVA
- Regression
Analysis of Variance (ANOVA) is a statistical test used when comparing the means of multiple groups. It assesses whether there are statistically significant differences between the group means, making option C the correct answer.
In NLP, which technique allows a model to pay different amounts of attention to different words when processing a sequence?
- One-Hot Encoding
- Word Embeddings
- Attention Mechanism
- Bag of Words (BoW)
The attention mechanism in NLP allows a model to pay different amounts of attention to different words when processing a sequence. This mechanism is a fundamental component of transformer-based models like BERT and GPT, enabling them to capture contextual information and understand word relationships in sentences, paragraphs, or documents.
In CNNs, the _______ layer is used to detect local features such as edges and textures.
- Convolutional
- Pooling
- Recurrent
- Fully Connected
The Convolutional layer in Convolutional Neural Networks (CNNs) is responsible for detecting local features in the input data, such as edges and textures. It does this by applying convolution operations across the input data, which allows the network to recognize spatial patterns in images or other structured data.
Which approach in recommender systems involves recommending items by finding users who are similar to the target user?
- Collaborative Filtering
- Content-Based Filtering
- Hybrid Filtering
- Matrix Factorization
Collaborative Filtering is a recommendation approach that identifies users similar to the target user based on their interactions and recommends items liked by those similar users. It relies on user-user similarity for recommendations.
Which algorithm is commonly used for predicting a continuous target variable?
- Decision Trees
- K-Means Clustering
- Linear Regression
- Naive Bayes Classification
Linear Regression is a commonly used algorithm for predicting continuous target variables. It establishes a linear relationship between the input features and the target variable, making it suitable for tasks like price prediction or trend analysis in Data Science.
In a data warehouse, the _________ table is used to store aggregated data at multiple levels of granularity.
- Fact
- Dimension
- Staging
- Aggregate
In a data warehouse, the "Fact" table is used to store aggregated data at various levels of granularity. These tables contain measures or metrics, which are essential for analytical queries and business intelligence reporting.