Regulatory Сompliance Quarter
Business Intelligence 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.
Contents
Outline
The predecessor lecture is Bookkeeping Quarter.
Concepts
- Business intelligence. Information that managers can use to make more effective strategic decisions.
- Association. A link between two elements or objects in a diagram.
- Systematic study. Looking at relationships, attempting to attribute causes and effects, and drawing conclusions based on scientific evidence.
- Data curation.
- 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.
- 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.
- Data manipulation.
- 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.
- Big data. The vast amount of quantifiable information that can be analyzed by highly sophisticated data processing.
Methods
- Data-analysis technique.
- Investigation. The formal or systematic examination of data sources that uses one or more data-gathering techniques and is conducted in order to gather data and/or assess data reliability.
Instruments
- Data-analysis tool.
- Database.
- Management information system (MIS). A system used to provide management with needed information on a regular basis.
- Digital tool. Technology, systems, or software that allow the user to collect, visualize, understand, or analyze data.
- Performance management system. Establishes performance standards used to evaluate employee performance.
Practices
The successor lecture is Enterprise Architecture Quarter.
