Chapter 5 ~ Business Intelligence – Flashcards
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Design Phase
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Decision makers construct a model for addressing the situation.
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Choice Phase
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Involves selecting a solution or course of action that seems best suited to resolve the problem.
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Problem Structure and the Nature of Decisions
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Various types of decisions can be placed along two major dimensions called:
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Problem Structure
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Decision-making processes fall along a continuum ranging from highly structured to highly unstructured.
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Structured decisions
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Deal with routine and repetitive problems for which standard solutions exist, such as inventory control.
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Minimizing costs and maximizing costs
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Two basic criteria used to evaluate solutions for Structured decisions are:
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Unstructured decisions
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Intended to deal with "fuzzy", complex problems for which there are no clear immediate decisions.
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Human intuition and judgement.
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Two basic criteria used to evaluate solutions for Unstructured decisions are:
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Semistructured decisions
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Deals with problems in which only some of the decision process phases are structured.
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A combination of standard solution procedures, and individual judgement.
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Two basic criteria used to evaluate solutions for Semistructured decisions are:
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Business Intelligence can make Structured decisions, but BI can not make Unstructured decisions.
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What is the main difference between Structured decisions and Unstructured decisions?
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Operational Control, Management Control, and Strategic Planning.
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The three categories that deals with the Nature of Decisions include:
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Operational Control
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Executing specific tasks efficiently and effectively. (Usually performed by lower-level managers.)
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Management Control
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Acquiring and using resources efficiently in accomplishing organizational goals. (Usually performed by middle managers and professional staff.)
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Strategic Planning
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The long-range goals and policies for growth and resource allocation. (Usually performed by Senior Executives.)
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MIS, statistical models (management science, financial, etc.)
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Which Information System supports Structured decisions?
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Decision support systems, business intelligence.
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Which Information System supports Semistructured decisions?
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Decision support systems, support systems, expert systems, enterprise resource planning, neural networks, business intelligence, big data.
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Which Information System supports Unstructured decisions?
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The Decision Matrix
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The combination of the three primary classes of problem structure and the three categories of the Nature of Decisions.
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Management Science or Operations Research
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The prescribed solutions that have been developed for each type of structured decision, which often include mathematical formulas.
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The Development of One or a Few Related BI Applications
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A point solution for a departmental need, organizations usually create a data mart to store the necessary data that can be integrated with data used elsewhere in the organization.
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The Development of Infrastructure to Support Enterprisewide BI
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An enterprise data warehouse is a crucial component of BI. Senior management often provides sponsorship, approval, and funding; considering it is an Enterprisewide initiative and can effect the whole organization.
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The Support for Organizational Transformation
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A company uses BI to fundamentally transform the ways it competes in the marketplace. BI supports a new business model, and enables the business strategy. This target is closely aligned with Corporate performance management or CPM.
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Corporate Performance Management (CPM)
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Involved with monitoring and managing an organization's performance according to KPIs (key performance indicators).
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Revenue, return on investment, overhead, and operational costs
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Examples of Key Performance Indicators (KPIs) include:
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Allows managers and analysts to analyze data to obtain valuable information and insights concerning the organization's KPIs
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What do BI applications that have to deal with CPM do?
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This section showed how important data warehouses and
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marts are to the different ways that organizations use BI.
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Multidimensional Analysis (Online Analytical Processing/OLAP), data mining, and decision support systems
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The Business applications used for analyzing data include:
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Multidimensional Analysis or Online Analytical Processing
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Involves "slicing and dicing" data stored in a dimensional format, drilling down in the data to greater detail, and aggregating the data.
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Rollup is a type of aggregation. (Ex: 2011-2013. As opposed to just the date 2011.)
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What is rollup?
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Data mining
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Refers to the process of searching for valuable business information in a large database, data warehouse, or data mart. Usually for identifying a business opportunity in order to create a sustainable competitive advantage.
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1. Predicting trends and behaviors, and 2. Identifying previously unknown patterns
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The two basic operations that Data mining can perform include:
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Data mining helps explain "why" something happened rather than "what" happened
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What is the difference between Data mining and the typical Business Application?
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By automating the process of finding predictive information in large databases
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How does Data mining predict trends and behaviors?
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Decision Support Systems (DSSs)
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Combines models and data to analyze Semistructured problems and some unstructured problems that involve extensive user involvement.
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Models
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Simplified representations, or abstractions, of reality.
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Sensitivity Analysis, What-If Analysis, and Goal-Seeking Analysis
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Related capabilities of Decision Support Systems include:
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Sensitivity Analysis
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The study of the IMPACT that CHANGES in one or more parts of a decision-making model have on other parts.
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Input variables, Output variables
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Most Sensitivity Analysis examine the impact that changes in _________________ have on ____________________.
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.Decision, Internal to the organization
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"What is our reorder point for these raw materials?" this is an example of a ________________variable, and is ______________ to the organization.
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Environmental, External to the organization
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"What will the rate of inflation be?" this is an example of a __________________variable, and is _______________ to the organization.
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It enables the system to adapt to changing conditions and to the varying requirements of different decision-making situations. As well as providing a better understanding of the model as well as the problem that the model purports to describe
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Why Is Sensitivity Analysis so valuable?
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What-If Analysis
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Attempts to predict the impact of a change in the assumptions (input data) on the proposed solution.
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What-If Analysis
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"What will happen to the total inventory cost if the originally assumed cost of carrying inventories is 12 percent rather than 10 percent" Which DSSs would best answer this question?
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Goal-Seeking Analysis
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Represents a "backward" solution approach by attempting to calculate the value of the inputs necessary to achieve a desired level of output.
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Goal-Seeking Analysis
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"An initial BI analysis predicted a profit of $2 million. Management might want to know what sales volume would be necessary to generate a profit of $3 million" Which DSSs would best answer this question?
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Dashboards
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Provides easy access to timely information and direct access to management reports. It is user friendly, supported by graphics, and enables managers to examine exception reports and drill down into detailed data.
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Dashboards
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Evolved from executive information systems, which were information systems designed specifically for the information needs of top executives
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Drill down, Critical Success Factors (CSFs), Status access, Key Performance Indicators, Trend analysis, Exception reporting.
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The Capabilities of Dashboards include:
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Drill down
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The ability to go to details, at several levels; it can be done by a series of menus or b clicking on a drillable portion of the screen.
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Critical Success Factors (CSFs)
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The factors most critical for the success of business. These can be organization, industry, departmental, or for individual workers.
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Key Performance Indicators (KPIs)
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The specific measures of CSFs.
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Status access
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The latest data available on KPI or some other metric.
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Trend analysis
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Short-, medium-, and long-term trend of KPIs or metrics, which are projected using forecasting methods.
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Exception reporting
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Reports that highlight deviations larger than certain thresholds. Reports may include only deviations.
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Data visualization
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The process of presenting data to users in visual formats such as texts, graphics, and tables; making IT applications more attractive and understandable to the user.
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Geographic Information Systems and Reality Mining
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Two valuable applications of Data visualization include:
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Geographic Information Systems (GIS)
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A computer-based system for capturing, integrating, manipulating, and displaying data using digitized maps.
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Geocoding
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The process of every record or digital object having an identified geographical location, enabling users to generate information for planning, problem solving, and decision making.
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Reality Mining
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A new type of technology that uses GISs and GPSs together allowing analysts to extract information from the usage patterns of mobile phones and other wireless devices.
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Real-Time BI
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Enables users to employ multidimensional analysis, data mining, and decision support systems to analyze data in real time.
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