FOR THE OPERSEA:
Quantitative Analysis
- provides data-driven analytical services for a range of business challenges, specializing in statistical models for site selection decisions.
- can assist by applying advanced statistical analysis techniques to help you get more from your data, as well as external data sources.
Decision Theory Method is an axiomatic system that contains at least one action axiom.
Stages in Decision Theory Method
- Formulation is the first and often most challenging stage in using formal decision methods (and in decision analysis in particular). The objective of the formulation stage is to develop a formal model of the given decision.
- Evaluation is the second and most algorithmic stage in using formal decision methods. The objective of the evaluation stage is to produce a formal recommendation (and its associated sensitivities) from a formal model of the decision situation.
- Formal Decision Methods third and last stage. The objective of the appraisal stage is for the decision maker to develop insight into the decision and determine a clear course of action. Much of the insight developed in this stage results from exploring the implications of the formal decision model developed during the formulation stage (i.e., from mining the model). Central to these implications is the formal recommendation for action calculated during the evaluation stage. Other implications include various forms of sensitivity of the recommendation to selected variables in the model. Additional insight is obtained by exposing key aspects of the reasoning that led to the formal decision model (i.e., by justifying the model). Possible actions following the appraisal stage include implementing the recommended course of action, revising the formal model and reevaluating it, or abandoning the analysis and doing something else.
Justifying a decision model is the action of exploring and explaining the reasoning that led to the formulation of a particular decision model.
Mining a decision model is the action of extracting information (e.g., sensitivity, value of information, and value of control) from a given decision model.
Decision Tree (or tree diagram) is a decision support tool that uses a tree-like graph or model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility. Decision trees are commonly used in operations research, specifically in decision analysis, to help identify a strategy most likely to reach a goal. Another use of decision trees is as a descriptive means for calculating conditional probabilities.
Example of Decision Tree:
A decision Tree consists of 3 types of nodes:
1. Decision nodes - commonly represented by squares
2. Chance nodes - represented by circles
3. End nodes - represented by triangles
Forecasting is the process of estimation in unknown situations. Prediction is a similar, but more general term. Both can refer to estimation of time series, cross-sectional or longitudinal data. Usage can differ between areas of application: for example in hydrology, the terms "forecast" and "forecasting" are sometimes reserved for estimates of values at certain specific future times, while the term "prediction" is used for more general estimates, such as the number of times floods will occur over a long period. Risk and uncertainty are central to forecasting and prediction.
Forecasting Procedures
• Determine the purpose and time: level of details, resources (manpower, computing times, etc), level of accuracy
• Establish a time horizon
• Select a forecasting technique
• Collect and analyze the data, and prepare the forecast, identify any assumptions
• Monitor the forecast
Linear programming
Mathematical modeling technique useful for guiding quantitative decisions in business, industrial engineering, and to a lesser extent the social and physical sciences. Solving a linear programming problem can be reduced to finding the optimum value (see optimization) of a linear equation (called an objective function), subject to a set of constraints expressed as inequalities. The number of inequalities and variables depends on the complexity of the problem, whose solution is found by solving the system of inequalities like a system of equations. The extensive use of linear programming during World War II to deal with transportation, scheduling and allocations of resources under constraints like cost and priority gave the subject an impetus that carried it into the postwar era. The number of equations and variables needed to model real-life situations accurately is large, and the solution process can be time-consuming even with computers.
FOR THE ADDBASE:
Stored Procedure is a subroutine available to applications accessing a relational database system. Stored procedures (sometimes called a proc, sproc, StoPro, or SP) are actually stored in the database data dictionary.
Typical uses for stored procedures include data validation (integrated into the database) or access control mechanisms. Furthermore, stored procedures are used to consolidate and centralize logic that was originally implemented in applications. Large or complex processing that might require the execution of several SQL statements is moved into stored procedures, and all applications call the procedures only.
Cursor (computers)
In computing, a cursor is an indicator used to show the position on a computer monitor or other display device that will respond to input from a text input or pointing device. The text cursor may be referred to as a caret in some cases. This term came about from older Unix systems that used the caret symbol as a text insertion indicator. The mouse cursor may be referred to as a mouse pointer, owing to its arrow shape on some systems.
Embedded SQL is a method of combining the computing power of a programming language and the database manipulation capabilities of SQL. Embedded SQL statements are SQL statements written inline with the program source code of the host language. The embedded SQL statements are parsed by an embedded SQL preprocessor and replaced by host-language calls to a code library. The output from the preprocessor is then compiled by the host compiler. This allows programmers to embed SQL statements in programs written in any number of languages such as: C/C++, COBOL and Fortran.
Database Trigger is procedural code that is automatically executed in response to certain events on a particular table in a database. Triggers can restrict access to specific data, perform logging, or audit data modifications.
There are two classes of triggers, they are either "row triggers" or "statement triggers". Row triggers define an action for every row of a table, while statement triggers occur only once per INSERT, UPDATE, or DELETE statement. Triggers cannot be used to audit data retrieval via SELECT statements.
Each class can be of several types. There are "BEFORE triggers" and "AFTER triggers" which identifies the time of execution of the trigger. There is also an "INSTEAD OF trigger" which is code that gets executed instead of the triggering statement.
There are typically three triggering events that cause triggers to 'fire':
- INSERT event (as a new record is being inserted into the database).
- UPDATE event (as a record is being changed).
- DELETE event (as a record is being deleted).
