12.11: Key Terms
- Page ID
- 94985
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\(\newcommand{\avec}{\mathbf a}\) \(\newcommand{\bvec}{\mathbf b}\) \(\newcommand{\cvec}{\mathbf c}\) \(\newcommand{\dvec}{\mathbf d}\) \(\newcommand{\dtil}{\widetilde{\mathbf d}}\) \(\newcommand{\evec}{\mathbf e}\) \(\newcommand{\fvec}{\mathbf f}\) \(\newcommand{\nvec}{\mathbf n}\) \(\newcommand{\pvec}{\mathbf p}\) \(\newcommand{\qvec}{\mathbf q}\) \(\newcommand{\svec}{\mathbf s}\) \(\newcommand{\tvec}{\mathbf t}\) \(\newcommand{\uvec}{\mathbf u}\) \(\newcommand{\vvec}{\mathbf v}\) \(\newcommand{\wvec}{\mathbf w}\) \(\newcommand{\xvec}{\mathbf x}\) \(\newcommand{\yvec}{\mathbf y}\) \(\newcommand{\zvec}{\mathbf z}\) \(\newcommand{\rvec}{\mathbf r}\) \(\newcommand{\mvec}{\mathbf m}\) \(\newcommand{\zerovec}{\mathbf 0}\) \(\newcommand{\onevec}{\mathbf 1}\) \(\newcommand{\real}{\mathbb R}\) \(\newcommand{\twovec}[2]{\left[\begin{array}{r}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\ctwovec}[2]{\left[\begin{array}{c}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\threevec}[3]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\cthreevec}[3]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\fourvec}[4]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\cfourvec}[4]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\fivevec}[5]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\cfivevec}[5]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\mattwo}[4]{\left[\begin{array}{rr}#1 \amp #2 \\ #3 \amp #4 \\ \end{array}\right]}\) \(\newcommand{\laspan}[1]{\text{Span}\{#1\}}\) \(\newcommand{\bcal}{\cal B}\) \(\newcommand{\ccal}{\cal C}\) \(\newcommand{\scal}{\cal S}\) \(\newcommand{\wcal}{\cal W}\) \(\newcommand{\ecal}{\cal E}\) \(\newcommand{\coords}[2]{\left\{#1\right\}_{#2}}\) \(\newcommand{\gray}[1]{\color{gray}{#1}}\) \(\newcommand{\lgray}[1]{\color{lightgray}{#1}}\) \(\newcommand{\rank}{\operatorname{rank}}\) \(\newcommand{\row}{\text{Row}}\) \(\newcommand{\col}{\text{Col}}\) \(\renewcommand{\row}{\text{Row}}\) \(\newcommand{\nul}{\text{Nul}}\) \(\newcommand{\var}{\text{Var}}\) \(\newcommand{\corr}{\text{corr}}\) \(\newcommand{\len}[1]{\left|#1\right|}\) \(\newcommand{\bbar}{\overline{\bvec}}\) \(\newcommand{\bhat}{\widehat{\bvec}}\) \(\newcommand{\bperp}{\bvec^\perp}\) \(\newcommand{\xhat}{\widehat{\xvec}}\) \(\newcommand{\vhat}{\widehat{\vvec}}\) \(\newcommand{\uhat}{\widehat{\uvec}}\) \(\newcommand{\what}{\widehat{\wvec}}\) \(\newcommand{\Sighat}{\widehat{\Sigma}}\) \(\newcommand{\lt}{<}\) \(\newcommand{\gt}{>}\) \(\newcommand{\amp}{&}\) \(\definecolor{fillinmathshade}{gray}{0.9}\)AD Hoc Reporting Tools: allow users to dive in and create their own reports, selecting fields, ranges, and other parameters to build their own reports on the fly..(12.8)
Big Data: Big data can be categorized by the three V’s: Volume (size), Variety (# of data types), and Velocity (processing speed). (12.2)
Business Intelligence: Describes the process that organizations take to collect and analyze data in the hopes of obtaining a competitive advantage. (12.6)
Canned Reports: Provide regular summaries of information in a predetermined format. They’re often developed by information systems staff and formats can be difficult to alter.(12.8)
Data Analytics: Looks at the past data to try and understand what happened and can also make predictions for the future.(12.6)
Data Governance: The commitment by an organization to ensuring data and information meet the characteristics of being valuable in order for the organization to meet its objectives.(12.7)
Data Mart: Database focused on addressing the concerns of a specific problem (e.g., increasing customer retention, improving product quality) or business unit (e.g., marketing, engineering).(12.9)
Data Mining: The process of analyzing data to find previously unknown and interesting trends, patterns, and associations in order to make decisions.(12.8)
Data Science: The analysis of large data sets to find new knowledge. The field of data science is constantly changing, and data scientists are on the cutting edge of work in areas such as artificial intelligence and neural networks. (12.6)
Data Warehouse: Set of databases designed to support decision making in an organization. It is structured for fast online queries and exploration. Data warehouses may extract, and aggregate enormous amounts of data from many different operational systems.(12.9)
Data Visualization: The graphical representation of information and data. These graphical representations (such as charts, graphs, and maps) can quickly summarize data in a way that is more intuitive and can lead to new insights and understandings. (12.8)
Dashboards: Type of data visualization that provide a heads-up display of critical indicators, letting managers get a graphical glance at key performance metrics. Some tools may allow data to be exported into spreadsheets. (12.8)
Decision-Making: The action or process of thinking through possible options and selecting one. (12.3)
Decision Support Systems: A computer program application that analyzes business data and presents it so that users can make business decisions more easily. (12.5)
Executive Information System (EIS):Customized for executives. These systems provide specific information for strategic decisions. For example, a CEO’s EIS may include special spreadsheets that present financial data comparing the company to its principal competitors and graphs showing current economic and industry trends.(12.5)
Expert System: Gives managers advice similar to what they would get from a human consultant. (12.5)
Legacy Systems: Are outdated information systems that were not designed to share data, aren’t compatible with newer technologies, and aren’t aligned with the organization’s current business needs.(12.7)
Online Analytical Processing: (OLAP)(pronounced “oh-lap”). Data used in OLAP reporting is usually sourced from standard relational databases, but it’s calculated and summarized in advance, across multiple dimensions, with the data stored in a special database called a data cube. (12.8)
Operational Decisions: Refer to decisions that employees make each day to make the organization run. For example, think about the restaurant that routinely offers a free dessert when a customer complaint is received. (12.4)
Semi-Structured Decision: one in which most of the factors needed for making the decision are known but human experience and other outside factors may still impact the decision (12.4)
Strategic Decisions: Set the course of an organization. Tactical/Managerial decisions are decisions about how things will get done. (12.4)
Structured Decision: One that is made quite often, and one in which the decision is based directly on the inputs.(12.3)
Unstructured Decision: Or non programmed decision involves a lot of unknowns.(12.4)