D-DS-FN-23 Dell Data Science Foundations Questions and Answers

A key business driver for Big Data analytics adoption is the ability to identify new business opportunities by analyzing large and complex datasets, which can provide valuable insights for decision-making and strategy development.

The decision tree having 17 layers and a leaf node with only three customers suggests that the tree is overfitting the data. This is because a deep tree with many layers can lead to overfitting, where the model fits the training data too closely, capturing noise and small details that do not generalize well to new data. Reducing the tree depth or pruning the tree can help mitigate overfitting.

In a user-defined aggregate function (UDAF), FFUNC refers to the optional final calculation function. It is used to perform any final calculation or transformation on the aggregated result before it is returned to the user.

The GROUP BY clause in the SQL statement implies the use of an aggregate function. In this case, avg(prod_cost) is an aggregate function that calculates the average of the product costs for each group of products.

A line chart is specifically designed to display time series data. It shows data points in a sequential order, making it easy to observe trends over time.

A box and whisker plot is ideal for visualizing the relationship between time spent and product category, especially when you have multiple categories. It shows the distribution of time spent in each product category, including the median, quartiles, and any potential outliers.

Linear regression is the appropriate technique for estimating a continuous target variable, such as home sale price, based on other continuous and categorical input variables like square footage, number of bedrooms, and lot size.

The Discovery phase involves understanding the business problem by conducting project sponsor interviews, gathering requirements, and drafting a problem statement to define the analytic objectives clearly.

The dependent variable in logistic regression is categorical, typically binary (e.g., success/failure, yes/no), since the goal is to model the probability of an event occurring.

When communicating project results to executives and the project sponsor, it's important to focus on business outcomes and benefits, ensuring they understand the value the project brings to the organization rather than the technical details.

The project goals component of a final presentation provides a succinct overview of the business situation that led to the initiation of the project. It sets the context for why the project was undertaken and what it aimed to achieve.

Regular expressions are highly useful for in-database text analysis, where they can be used to search, match, and manipulate text data efficiently within databases, especially for tasks like pattern matching, data extraction, and validation.

An Excel file is an example of quasi-structured data because it contains structured data (like rows and columns) but may have irregularities, such as varying data formats, missing headers, or mixed data types within cells, making it less strictly structured than a relational database.

Multinomial logistic regression should be used when the dependent variable has more than two categories (i.e., it is categorical with more than two possible outcomes). This differs from binary logistic regression, which is used when the dependent variable is binary (i.e., has two categories).