In text analysis, _______ is a common preprocessing step to reduce the dataset to its most basic form.
- Bag of Words
- Lemmatization
- Regularization
- Tokenization
Bag of Words is a common preprocessing step in text analysis, where the dataset is represented as an unordered set of words, disregarding grammar and word order. Lemmatization, Tokenization, and Regularization are distinct processes in text analysis.
How does data lineage impact data governance and quality?
- It has no impact on data governance and quality.
- It helps track the flow of data from its origin to destination, promoting transparency and trust in data.
- It limits access to data, improving security.
- It only impacts data governance but not data quality.
Data lineage is crucial for understanding the flow and transformation of data across systems. It enhances data governance by providing transparency into data sources, transformations, and destinations, thus improving data quality by enabling traceability and accountability.
In a case study where a business is expanding into new markets, which analysis technique is best for understanding the competitive landscape?
- Competitor Analysis
- Gap Analysis
- PESTLE Analysis
- SWOT Analysis
Competitor Analysis is the most suitable technique for understanding the competitive landscape when a business is expanding into new markets. It involves evaluating the strengths and weaknesses of competitors to identify opportunities and threats. SWOT and PESTLE analyses focus on broader factors and may not provide as detailed competitor insights.
To enhance user interaction, a dashboard may include _______ elements such as dropdowns or sliders for dynamic data viewing.
- Animated
- Colorful
- Interactive
- Static
To enhance user interaction, a dashboard may include Interactive elements such as dropdowns or sliders. These elements allow users to dynamically view and analyze data, providing a more engaging and user-friendly experience.
How does Principal Component Analysis (PCA) assist in data preprocessing?
- It increases data complexity by adding more features
- It reduces dimensionality by transforming variables into a new set of uncorrelated variables, known as principal components
- It removes outliers from the dataset
- It standardizes the data by scaling it to a specific range
PCA assists in data preprocessing by reducing dimensionality. It transforms the original variables into a new set of uncorrelated variables, known as principal components, preserving essential information while reducing computational complexity.
Which cloud computing service model provides users with the highest level of control over the operating systems, applications, and storage?
- Function as a Service (FaaS)
- Infrastructure as a Service (IaaS)
- Platform as a Service (PaaS)
- Software as a Service (SaaS)
Infrastructure as a Service (IaaS) provides users with the highest level of control over the operating systems, applications, and storage. Users can manage and control the underlying infrastructure while still benefiting from the cloud environment.
Which project management methodology is often favored in data projects for its flexibility and iterative approach?
- Agile
- PRINCE2
- Scrum
- Waterfall
Agile is often favored in data projects for its flexibility and iterative approach. It allows teams to adapt to changing requirements and promotes continuous improvement throughout the project lifecycle. Waterfall, Scrum, and PRINCE2 have different methodologies and are not as commonly associated with the iterative nature of data projects.
In risk management for data projects, the process of identifying, analyzing, and responding to risk factors is known as _________ management.
- Data
- Project
- Risk
- Stakeholder
In risk management, the process of identifying, analyzing, and responding to risk factors is known as "Risk" management. This involves assessing potential risks to the success of a data project and developing strategies to mitigate or respond to them.
For time series data manipulation in Pandas, which method is best suited for resampling data at different frequencies?
- aggregate()
- groupby()
- pivot_table()
- resample()
The resample() method in Pandas is specifically designed for time series data manipulation, allowing you to resample data at different frequencies (e.g., daily to monthly) efficiently. The groupby(), aggregate(), and pivot_table() methods serve different purposes in data manipulation.
A _______ distribution is a common probability distribution used in statistics, which is symmetrical and bell-shaped.
- Binomial
- Exponential
- Normal
- Poisson
A Normal distribution, also known as a Gaussian distribution, is symmetrical and bell-shaped. It is widely used in statistics to model various natural phenomena and forms the basis for many statistical methods.