Business Analytics Chapter 1 – Vocabulary

Vocabulary flashcards covering key terms from Chapter 1: Introduction to Business Analytics.

Strategic decisions

High-level choices that set an organization’s overall direction, goals, and aspirations.

Tactical decisions

Mid-level choices that specify how to achieve strategic goals; usually handled by middle management.

Operational decisions

Day-to-day choices that determine how the firm runs; typically made by operations managers closest to customers.

Decision-making process

A five-step approach: (1) identify/define the problem, (2) set evaluation criteria, (3) list alternatives, (4) evaluate alternatives, (5) choose an alternative.

Alternative solutions

The different courses of action identified and compared during decision making.

Business analytics

The scientific process of transforming data into insight to support better decisions.

Descriptive analytics

Techniques that summarize and describe what has happened in the past (e.g., reports, dashboards, descriptive statistics).

Predictive analytics

Techniques that use historical data to forecast future events or estimate variable impacts (e.g., regression, time-series, supervised data mining, simulation).

Prescriptive analytics

Techniques that recommend actions by combining predictions with rules or optimization to identify the best course of action.

Data query

A request for information with specific characteristics extracted from a database.

Data dashboard

A visual display—tables, charts, maps, stats—updated in real time to monitor key metrics.

Unsupervised learning

Data-mining methods that uncover patterns in unlabeled data without predefined targets.

Cluster analysis

An unsupervised technique that groups observations based on similarity.

Association rules

Unsupervised techniques that find items or events that co-occur (correlate) within data.

Supervised learning

Data-mining methods that learn relationships between input variables and known outcomes to make predictions.

Linear regression

A predictive model that estimates the relationship between a dependent variable and one or more independent variables.

Time series analysis

Techniques that model and forecast data collected sequentially over time.

Simulation

The use of probability and statistics to create computer models that study the impact of uncertainty on decisions.

Optimization model

A mathematical model that identifies the best decision by maximizing or minimizing an objective subject to constraints.

Simulation optimization

The combination of simulation and optimization to find good decisions in complex, uncertain environments.

Decision analysis

A prescriptive framework for choosing optimal strategies when facing multiple alternatives and uncertain events.

Utility theory

A branch of decision analysis that assigns values to outcomes based on a decision maker’s risk preference.

Big data

Data sets too large or complex for conventional processing tools and desktop software.

Four Vs of Big Data

Characteristics of big data: Volume, Velocity, Variety, and Veracity.

Hadoop

An open-source environment that enables distributed storage and processing of big data across clusters.

MapReduce

Hadoop’s programming model that performs a ‘map’ step to process data and a ‘reduce’ step to aggregate results.

Cloud computing

Using remote servers via the internet to store and process data and run applications.

Data security

Protecting stored data from destructive forces or unauthorized access.

Artificial intelligence (AI)

Systems that use big data and computing power to perform tasks that previously required human intelligence.

Data scientist

A professional trained in computer science and statistics who processes and analyzes massive data sets.

Financial analytics

Use of descriptive, predictive, and prescriptive tools to monitor performance, manage risk, and optimize portfolios in finance.

HR analytics (People analytics)

Applying analytics to employee data to improve hiring, retention, productivity, and diversity.

Marketing analytics

Applying analytics to understand consumer behavior and optimize advertising, pricing, and product decisions.

Sentiment analysis

Text analytics that gauges customer opinions or emotions to monitor the ‘voice of the customer.’

Supply-chain analytics

Analytics applied to logistics and supply networks to enhance efficiency, quantify risk, and plan resilient operations.

Data breach

An unauthorized use, disclosure, or theft of confidential data.

General Data Protection Regulation (GDPR)

EU privacy law (2018) that requires clear consent, specifies data use, grants data access & erasure rights to individuals.

INFORMS Ethics Guidelines

Professional principles urging analytics practitioners to be accountable, honest, objective, respectful, and socially responsible.