Business Analysis. Introduction to data modeling
Lesson 3: An introduction to data modeling
3.1 Introduction: The importance of conceptual models same: understand the problem before you start constructing a solution. There are two important things to keep in mind when learning about and doing data modeling: 1. Data modeling is first and foremost a tool for communication.Their is no single “right” model. Instead, a valuable model highlights tricky issues, allows users, designers, and implementors to discuss the issues using the same vocabulary, and leads to better design decisions. 2. The modeling process is inherently iterative: you create a model, check its assumptions with users, make the necessary changes, and repeat the cycle until you are sure you understand the critical issues. In this background lesson, you are going to use a data modeling technique—specifically, EntityRelationship Diagrams (ERDs)—to model the business scenario from Lesson 2. The data model you create in this lesson will form the foundation of the database that you use throughout the remaining lessons.
Before you sit down in front of the keyboard and start creating a database application, it is critical that you take a step back and consider your business problem—in this case, the kitchen supply scenario presented in Lesson 2— from a conceptual point of view. To facilitate this process, a number of conceptual modeling techniques have been developed by computer scientists, psychologists, and consultants.
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For our purposes, we can think of a conceptual model as a picture of the information system we are going to build. To use an analogy, conceptual models are to information systems what blueprints are to buildings.
There are many different conceptual modeling techniques used in practice. Each technique uses a different set of symbols and may focus on a different part of the problem (e.g., data, processes, information flows, objects, and so on). Despite differences in notation and focus, however, the underlying rationale for
3.1 Introduction: The importance of conceptual models same: understand the problem before you start constructing a solution. There are two important things to keep in mind when learning about and doing data modeling: 1. Data modeling is first and foremost a tool for communication.Their is no single “right” model. Instead, a valuable model highlights tricky issues, allows users, designers, and implementors to discuss the issues using the same vocabulary, and leads to better design decisions. 2. The modeling process is inherently iterative: you create a model, check its assumptions with users, make the necessary changes, and repeat the cycle until you are sure you understand the critical issues. In this background lesson, you are going to use a data modeling technique—specifically, EntityRelationship Diagrams (ERDs)—to model the business scenario from Lesson 2. The data model you create in this lesson will form the foundation of the database that you use throughout the remaining lessons.
Before you sit down in front of the keyboard and start creating a database application, it is critical that you take a step back and consider your business problem—in this case, the kitchen supply scenario presented in Lesson 2— from a conceptual point of view. To facilitate this process, a number of conceptual modeling techniques have been developed by computer scientists, psychologists, and consultants.
?
For our purposes, we can think of a conceptual model as a picture of the information system we are going to build. To use an analogy, conceptual models are to information systems what blueprints are to buildings.
There are many different conceptual modeling techniques used in practice. Each technique uses a different set of symbols and may focus on a different part of the problem (e.g., data, processes, information flows, objects, and so on). Despite differences in notation and focus, however, the underlying rationale for