Relationships are everywhere: between people, between organizations, between organizations and people. Think about being an employee of a company, being a member of a project team, or being a subsidiary of another company. Is there a straightforward way to accurately model and manage all these relationships? Can we easily answer the question ‘Who knows who?’ A Quick Review of Relationships Exactly how this basic model was derived was described in my previous article, Flexible and Manageable Bill of Materials (BOM) Designs.
The bill of materials design pattern is deceptively simple, yet incredibly powerful. This article will introduce an example, familiar to IT professionals, that you may not have thought fits the BOM pattern. It will also introduce concepts to show you how to make your BOM structures more flexible and much easier to manage. A Short Recap of the BOM A bill of materials has its roots in manufacturing. It is a list of the raw materials, sub-assemblies, intermediate assemblies, sub-components, parts, and the quantities of each needed to manufacture an end product.
The bill of materials (BOM) design pattern is deceptively simple, yet incredibly powerful. Historically, it’s been employed to model product structures, but the pattern can be used to do much more than simply define a hierarchy. This article will introduce three very different examples to help you to recognize the pattern in your own projects. What Is a Bill of Materials, or BOM? A bill of materials has its roots in manufacturing.
The first part of this series introduced some basic steps for managing the lifecycle of any entity in a database. Our second and final part will show you how to define the actual workflow using additional configuration tables. This is where the user is presented with allowable options each step of the way. We’ll also demonstrate a technique for working around the strict reuse of ‘assemblies’ and ‘sub-assemblies’ in a Bill of Materials structure.
Have you ever come across a situation where you need to manage the state of an entity that changes over time? There are many examples out there. Let’s start with an easy one: merging customer records. Suppose we are merging lists of customers from two different sources. We could have any of the following states arise: Duplicates Identified – the system has found two potentially duplicate entities; Confirmed Duplicates – a user validates the two entities are indeed duplicates; or Confirmed Unique – the user decides the two entities are unique.