Importance of Information

• Contextualizing Data: Information provides context to raw data, enabling better understanding and decision-making.

• Decision Making: Good, timely, and relevant information is crucial for making informed decisions in any organization.

• Competitive Edge: Companies need accurate information to stay ahead of competitors.

• Organizational Survival: Reliable information is necessary for a company’s survival in a competitive global environment.

Data Inconsistency in Databases

• Definition: Data inconsistency occurs when there are different and conflicting versions of the same data in multiple places within a database.

• Examples: An example provided was a department ID showing both 100 and 4 for the accounting department, which creates confusion and reduces reliability.

• Impact: Data inconsistency generates unreliable information, which can lead to bad decisions and operational issues in database management systems (DBMS).

• Data Redundancy: Inconsistent data often arises from data redundancy, especially in many-to-many relationships that should be avoided in data modeling.

Types of Databases in Work Environments

• Transactional Database (e.g., Banner at GMU): Used to track transactions such as sales, payments, and daily operations.

  • Real-Time Data: Transactions must be recorded immediately and accurately; they are time-critical.

  • Example: When a student registers for a course or makes a payment at GMU, this data is recorded in Banner.

• Data Warehouse: Primarily focused on storing data for generating strategic information, typically not real-time.

  • ETL Process: A scheduled ETL (Extract, Transform, Load) team pulls data from Banner into the data warehouse overnight.

  • Reporting: Reports are generally generated from the data warehouse, and the data may be one day behind the transactional database.

  • Critical Data: Only essential data for decision-making is stored in the warehouse, avoiding the storage of excessive data from the transactional database.

Understanding Data Security and Policies

• Data Security Training: Employees are required to understand the importance and security of GMU’s data to protect sensitive client information.

• Common Definitions/Policies: Policies exist to ensure all employees understand key data terminology and practices effectively to maintain uniformity across the organization.

Entity Relationship Diagram (ERD) and Its Importance

• Definition of ERD: An ERD is a graphical representation used in data modeling to illustrate the relationships between different entities in a database.

• Components of an ERD:

  • Entities: Objects or concepts represented in the database (e.g., students, courses).

  • Attributes: Characteristics or properties of entities.

  • Keys: Unique identifiers used in the database.

  • Relationships: Connections between entities (e.g., one-to-many relationships).

• Business Rules: Essential for ensuring a correctly defined database and minimizing risks of poorly structured applications.

  • Gathering Business Rules: Before building a database, business rules must be collected to ensure all requirements are understood and addressed.

Importance of Database Design

• Proper Design: Effective design and data definition are critical for building a robust database that meets the operational needs of an organization.

• Consequences of Poor Design: A poorly defined database based on incorrect or incomplete business rules can lead to ineffective applications and wasted resources.