DMC Study Guide 2026

Drilling down moves from higher-level summaries to more detailed data — for example, from annual sales totals down to individual daily transactions.

The median is least affected by outliers because it represents the positional middle value, not influenced by extreme values on either end.

Data visualization is the graphical representation of information and data, using visual elements like charts, graphs, and maps. Its primary purpose is to make complex datasets more accessible, understandable, and digestible, allowing users to quickly identify trends, patterns, and insights. Effective visualization facilitates better decision-making by presenting data in an intuitive and impactful way.

Gradient descent is an optimization algorithm used to minimize the loss function of a model by iteratively adjusting its parameters (weights and biases). It calculates the gradient of the loss function with respect to each parameter and moves in the direction opposite to the gradient, effectively finding the steepest path downwards. This iterative process helps the model converge to the optimal set of parameters that yield the lowest prediction error.

Support Vector Machines (SVMs) are powerful supervised learning models primarily used for classification tasks. Their core function is to find an optimal hyperplane that distinctly separates data points belonging to different classes in a high-dimensional space. The goal is to maximize the margin between the classes, which improves the model's generalization ability to new, unseen data.

NER identifies and classifies real-world entities such as persons, organizations, and locations within text.