Business Spreadsheet Modeling Exam 1 (ch. 1,2,3)

Algorithm

A logical, step‑by‑step procedure used to solve a problem or perform a computation.

Big Data

Extremely large and diverse data sets that require advanced methods to capture, store, manage, and analyze.

Business analytics

The use of data, statistical analysis, and models to drive business decisions and improve performance.

Business intelligence

Technologies and systems that gather, store, and report data to support managerial decision making.

Constraint

A limitation or requirement that restricts the possible solutions in a decision model.

Data mining

Techniques for discovering patterns, relationships, and insights from large data sets.

Decision Model

A mathematical or logical representation of a problem used to evaluate decision alternatives.

Decision Options

The controllable inputs or choices in a decision model that determine outcomes.

Decision Support Systems

Computer‑based tools that help managers make better decisions through data, models, and analysis.

Descriptive analytics

Methods that summarize and interpret historical data to understand what has happened.

Deterministic model

A model in which all inputs are known with certainty and outcomes are fully determined.

Information systems

Integrated systems that collect, process, store, and distribute information to support operations and decisions.

Model

A simplified representation of a real system used to analyze behavior, test scenarios, or support decisions.

Modeling and optimization

The process of building models and using mathematical techniques to find the best possible solution.

Objective function

The mathematical expression that defines what is being maximized or minimized in an optimization model.

Operations Research

A discipline that applies mathematical modeling and analytical methods to improve decision making.

Optimization

The process of finding the most effective solution under given constraints.

Predictive analytics

Techniques that use historical data and models to forecast future outcomes.

Prescriptive analytics

Methods that recommend actions by combining data, models, and optimization.

Price elasticity

A measure of how sensitive demand is to changes in price.

Stochastic model

A model that incorporates randomness or uncertain inputs.

What-if analysis

The process of changing model inputs to examine how outcomes respond.

A regional hospital is struggling with patient wait times in its emergency department. The issue is most severe during evenings and weekends, when patient inflow spikes unpredictably. The hospital has enough doctors and nurses overall, but staffing schedules are fixed and do not account for fluctuations. Administrators want to reduce wait times without significantly increasing labor costs.

How might business analytics help the hospital improve patient flow? What data would be needed to support effective decisions?

Business analytics can help by identifying patterns in patient arrivals and aligning staff schedules with demand.

Descriptive analytics: Summarize historical patient arrival data by time of day, day of week, and season. This reveals when bottlenecks occur.

Predictive analytics: Forecast patient inflows using past trends, holidays, and local event data. This helps anticipate surges.

Prescriptive analytics: Optimize staff scheduling models to minimize wait times while controlling costs. Simulation can test different staffing scenarios.

Data set

a collection of date

Database

a collection of related data containing records on people, places, and things (provides structure)

Empirical data

Data obtained through observation, measurement, or real-world experience

Logical functions

Functions that evaluate conditions and return TRUE/FALSE or conditional results, such as IF, AND, OR

Lookup Functions

Functions that search for values in a table and return related information, VLOOKUP, HLOOKUP

Pareto analysis

a technique that identifies the most significant factors in a day set, often using the 80/20 rule

Pivot Tables

Excel tools that summarize, analyze, and reorganize large data sets dynamically

Slicers

Visual filtering tools that allow users to quickly filter PivotTables or tables using clickable buttons

Area Chart

Shows quantitative data over time with the area under the line filled in

When is an area chart best used

When you want to emphasize total volume over time or you’re comparing cumulative trends across categories

Bar Chart

Uses horizontal bars to compare categories

When is it best to use bar charts

When comparing discrete categories like regions and products, or you want clear ranking or magnitude differences

Bubble Chart

A scatterplot with a third variable represented by bubble size

When is it best to use bubble charts

When you need to show three variables at once or you want to highlight relative magnitude (bubble size)

Color Scales

Conditional formatting that shades cells based on value intensity

Column chart

Vertical bars comparing categories

When are column charts best used

When comparing frequency or magnitude across categories, wanting to show changes over time with discrete periods, or a simple, universally understood chart.

Combination Chart

Mixes two chart types (often column + line)

When are combination charts best used

When you’re comparing different data types like sales vs. profit margin, one variable needs a secondary axis, or you want to show relationships between volume and trend