Bookkeeping Quarter

Organizational Learning Quarter (hereinafter, the Quarter) is the first of four lectures of Operations Quadrivium (hereinafter, the Quadrivium):

• The Quarter is designed to introduce its learners to enterprise discovery, or, in other words, to concepts related to obtaining data needed to administer the enterprise effort; and
• The Quadrivium examines concepts of administering various types of enterprises known as enterprise administration as a whole.

The Quadrivium is the first of seven modules of Septem Artes Administrativi, which is a course designed to introduce its learners to general concepts in business administration, management, and organizational behavior.

Outline

The predecessor lecture is Workteam Leadership Quarter.

Concepts

1. Learning. Any relatively permanent change in behavior that occurs as a result of experience.
   • Lessons learned. The learning gained from the process of performing the project. Lessons learned may be identified at any point.
   • Lessons learned process. A process improvement technique used to learn about and improve on a process or project. A lessons learned session involves a special meeting in which the team explores what worked, what didn't work, what could be learned from the just-completed iteration, and how to adapt processes and techniques before continuing or starting anew.
2. Data research.
   • Qualitative research.
   • Quantitative research.
3. Data structure.
   • Structured data.
   • Unstructured data.
   • Data validation.
4. Data model. An analysis model that depicts the logical structure of data, independent of the data design or data storage mechanisms.
   • Optionality. Defining whether or not a relationship between entities in a data model is mandatory. Optionality is shown on a data model with a special notation.
   • Cardinality. The number of occurrences of one entity in a data model that are linked to a second entity. Cardinality is shown on a data model with a special notation, number (e.g., 1), or letter (e.g., M for many).
   • Data flow diagram (DFD). An analysis model that illustrates processes that occur, along with the flows of data to and from those processes.
   • State diagram. An analysis model showing the life cycle of a data entity or class.
   • Sequence diagram. A type of diagram that shows objects participating in interactions and the messages exchanged between them.
   • Class model. A type of data model that depicts information groups as classes.
5. Data dictionary. An analysis model describing the data structures and attributes needed by the system.
   • Data entity. A group of related information to be stored by the system. Entities can be people, roles, places, things, organizations, occurrences in time, concepts, or documents.
   • Attribute. A data element with a specified data type that describes information associated with a concept or entity.
   • Glossary. A list and definition of the business terms and concepts relevant to the solution being built or enhanced.
   • Jargon. Specialized terminology or technical language that members of a group use to communicate among themselves.
6. Categorization.
   • Structural rule. Structural rules determine when something is or is not true or when things fall into a certain category. They describe categorizations that may change over time.
   • Knowledge area. A group of related tasks that support a key function of business analysis.
7. Repository. A real or virtual facility where all information on a specific topic is stored and is available for retrieval.
   • Interoperability. Ability of systems to communicate by exchanging data or services.

Results

1. Knowledge base.

Practices

The successor lecture is Business Intelligence Quarter.