IS 2000 Kees Van Hemmen

This week we continued our discussion of Information Based Processes and Process Analytics. Specifically, we discussed Process Time Analysis. Process Time Analysis is the calculation of the execution time and cost of a process, using expected cost to account for branching. This must first be done via a time study. Time studies measure how long each activity in a process takes, how long a unit has to wait before processing starts, and then sum the processing and wait time to get flow time. Time studies take branching into account by identifying the likelihood of each branch occurring. Execution time is generally estimated by either observation or random sampling. Alternatively, several experts can be called in to give estimates, followed by a delphi analysis that will weight each of these estimates and provide a master estimate. This is known as single band delphi. Alternatively, wide band delphi can be employed. This is where each expert provides a pessimistic, optimistic, and expected...

This week in class we covered information based processes, information flows, and process analytics. There are two prominent ways to model information flows. Every information based process has a couple of inalienable traits: an explicit and measurable goal, specific inputs in the form of information, specific outputs in the form of new information, the use of resources, and having an effect on multiple organizational units. Data is generally modeled via Data Flow Diagrams, whereas activities are generally modeled through Flow Charts. The first thing an analyst must do when modeling a process is identify where the process begins and where it ends. If it is ever unclear how detailed a process should be, an analyst should air on the side of generality, choosing instead to refer to subprocesses that can in turn be modeled on their own. In the modeling of processes, different actors become involved. Popular actors include customers, employees, suppliers, and regulatory agencies. Process mo...

This week in class we discussed and studied decision trees and their application in dealing with uncertainty in decision making. Decision trees are useful because the analysis of complex decisions with significant uncertainty can be confusing for a variety of reasons. First, and most importantly, the consequence that will result from selecting any specified decision alternative cannot be predicted with certainty. Not only this, but there are also often a large number of different factors that must be taken into account when making a decision. Finally, a decision maker's attitude toward risk taking can impact the relative desirability of different alternatives. Decision tree diagrams are read from left to right. The leftmost node in a decision tree is called the root node. The branches emanating to the right from a decision node represent the decisions that can be made from that node. Only one of these alternatives can be selected. The small circles in the tree are called chance nod...

During weeks 7 and 8 we focused on SQLite and R usage for data storage and retrieval. SQLite creates and stores relational databases. In SQL, fields can be referred to as columns, whereas rows are records. A table is a set of records. In SQL, we are generally concerned with creating records. Tables store records that are described by the columns that their rows contain. In order to manipulate information in tables we use either DDL or DML, aka data definition language and data manipulation language. DDL is used to establish the fields and rows for tables, so as to structure and initialize the data. Meanwhile, DML is used to alter what is in those fields. DML is largely what we call "querying", wherein we make queries of a table looking for different data responses. Common examples of these queries include SHOW_DATABASES and SHOW_TABLES, which, respectively, return the databases and tables in a SQL file. If you wish to see the columns from a given table or database, SHOW COLUM...

This week in class we worked largely with Excel manipulation and usage. We worked on basics like column naming and data input, but then moved on to more sophisticated data manipulation measures. We first learned count and sum functions. These tally the values of a set of cells automatically, decreasing the processing time of data. We also learned how to implement excels logical functions like IF, AND, and OR, which allow for conditional commands to be applied to data in order to manipulate only select data points. Cell references were also covered, with the distinctions between absolute, relative, and mixed references particularly emphasized. Relative references change when they are pasted or filled, whereas absolute references do change, as they are hardcoded to a given cell. Entry of dates and times using slashes, dashes, and colons were also reviewed. Text functions, such as those that allow for the synthesis of two different string cells, were also covered and included. Lookup func...

This week we worked on building XML files. XML is extensible markup language. XML is a tag based syntax, in a manner similar to HTML. However, there are some key differences between XML and HTML. HTML uses specific tags, whereas XML is extensible by nature, allowing you to make your own tags and in turn customize and expand your data structure. It is used in a variety of technologies, like RSS. However, it is also used to convert older data storage mediums to newer databases, thus allowing older information to be integrated seamlessly into a new system. The primary objective of XML is to structure and describe information. For instance, an XML structure could describe a nuclear family. The family could be the parent tag, while attributes might be mother, father, son, daughter, dog, and cat, as well as house. Dog and cat may be qualified as optional structures. XML has several advantages and disadvantages. Among its advantages is that it allows for data to be stored separate from its pr...