Business Analytics
prescriptive analytics
Techniques that analyze input data and yield a best course of action.
utility theory
The study of the total worth or relative desirability of a particular outcome that reflects the decision maker's attitude toward a collection of factors such as profit, loss, and risk.
simulation optimization
The use of probability and statistics to model uncertainty, combined with optimization techniques, to find good decisions in highly complex and highly uncertain settings.
Operational decisions
affect how the firm is run from day to day; they are the domain of operations managers, who are the closest to the customer.
Data dashboard
collections of tables, charts, maps, and summary statistics that are updated as new data become available. Dashboards are used to help management monitor specific aspects of the company's performance related to their decision-making responsibilities.
Strategic decision
A decision that involves higher-level issues and that is concerned with the overall direction of the organization, defining the overall goals and aspirations for the organization's future.
optimization models
A mathematical model that gives the best decision, subject to the situation's constraints.
rule-based model
A prescriptive model that is based on a rule or set of rules.
decision analysis
A technique used to develop an optimal strategy when a decision maker is faced with several decision alternatives and an uncertain set of future events.
big data
Any set of data that is too large or too complex to be handled by standard data-processing techniques and typical desktop software.
Decision making process
Identify and define the problem. Determine the criteria that will be used to evaluate alternative solutions. Determine the set of alternative solutions. Evaluate the alternatives. Choose an alternative.
Tactical decision
concern how the organization should achieve the goals and objectives set by its strategy, and they are usually the responsibility of midlevel management. Tactical decisions usually span a year and thus are revisited annually or even every six months.
Predictive analytics
consists of techniques that use models constructed from past data to predict the future or ascertain the impact of one variable on another. For example, past data on product sales may be used to construct a mathematical model to predict future sales.
3 categories of analytics
descriptive analytics, predictive analytics, and prescriptive analytics.
Descriptive analytics
encompasses the set of techniques that describes what has happened in the past. Examples are data queries, reports, descriptive statistics, data visualization including data dashboards, some data-mining techniques, and basic what-if spreadsheet models.
Simulation
involves the use of probability and statistics to construct a computer model to study the impact of uncertainty on a decision. For example, banks often use simulation to model investment and default risk in order to stress-test financial models.
data query
is a request for information with certain characteristics from a database. For example, a query to a manufacturing plant's database might be for all records of shipments to a particular distribution center during the month of March. This query provides descriptive information about these shipments: the number of shipments, how much was included in each shipment, the date each shipment was sent, and so on.
Business analytics
the scientific process of transforming data into insight for making better decisions.Footnote Business analytics is used for data-driven or fact-based decision making, which is often seen as more objective than other alternatives for decision making.
Data mining
the use of analytical techniques for better understanding patterns and relationships that exist in large data sets. For example, by analyzing text on social network platforms like Twitter, data-mining techniques (including cluster analysis and sentiment analysis) are used by companies to better understand their customers.