Logical Data Modeling is an essential component of professional business analysis. Logical data modeling is often mistaken for database design. However, logical data modeling is the foundation for excellence in business analysis, business systems analysis and business intelligence requirements analysis.
Inteq’s Logical Data Modeling training course provides the basis for understanding the complex moving parts of an organization - its data-oriented business rules - the foundation for precision and agility in requirements analysis.
Business terminology embodies an organization’s business concepts, rules and underlying relationships. These concepts, rules and relationships form a body of knowledge called “data-oriented business rules.”
In most organizations, data-oriented business rules live as tribal knowledge, informally, in the minds of the people doing the essential day-to-day work of the organization.
However, these informal rules unofficially govern how organizations operate and how decisions are made. These rules are surprisingly vague and ambiguous; they are rarely subject to critical analysis. Yet, these rules are the basis for articulating business system requirements that are equally vague and ambiguous.
Vague, ambiguous, incomplete, incorrect, inflexible, missing business rules result in:
• Systems that are ridged and rapidly become obsolete and ineffective.
• Non-productive time spent on “work-arounds” to compensate for lack of functionality.
• Business processes that are cumbersome and inflexible.
• Costly, inflexible and maintenance-intensive information systems; systems, that even after significant investment, still do not deliver the necessary functionality.
That’s truly unfortunate because there is a clear path to getting the requirements right. Based on decades of experience, Inteq has uncovered and refined the foundational patterns of data-oriented business rules. Participants in Inteq's Logical Data Modeling training course utilize these patterns to rapidly discover, critically analyze and precisely specify data-oriented business rules via entity relationship (ER) diagrams.
Inteq's Logical Data Modeling results in the specification of data-oriented business rules that:
• Are thorough, clear and accurate. Data-oriented business rules that fully support business and user requirements.
• Scale to support the enterprise. Data-oriented business rules are often more complex at the enterprise level than they initially appear at the departmental or business unit level.
• Enable organizational agility. Rules that can adapt and evolve over time. Data-oriented business rules that transcend specific project solutions to seamlessly adapt to future requirements as the organization evolves.
• Support business intelligence. Data-oriented business rules must be thorough and accurate to enable effective tactical and strategic decisions.
