Data Design Overview

The term data refers to the entire collection of information stored in your directory service. We also use data as a general term to refer to information of any kind regardless of where it is stored. Data is what makes a directory service interesting; after all, your directory service is only as useful as the data it holds. Furthermore, the issues surrounding data sometimes evoke strong emotional and political responses because people care about their personal information, their department's information, customer information, and Web site visitor information. In addition, people who write or deploy directory-enabled applications have their own data- related needs. Some of the different needs will inevitably conflict, so data design is an important and potentially complex area.

Some other data-related topics are explored in other chapters. For example, when designing a schema (see Chapter 8, Schema Design), we will use the results obtained in this chapter to choose LDAP object classes and attributes to hold your data. The design of your directory's namespace (see Chapter 9, Namespace Design) will also build on the material in this chapter as you strive to organize your directory data in a logical structure to optimize administration and operation of the directory service. In Chapter 18, Maintaining Data, we will explore topics related to keeping your directory data up-to-date and accurate over the lifetime of your directory service.

In Chapter 6, Defining Your Directory Needs, we examined directory needs in detail, focusing on the applications that will use your directory. As already noted, the applications deployed against your directory greatly influence the design and deployment of the entire directory service. Applications are the strongest driving factor in identifying which pieces of data should be stored in your directory and how you should manage them.

The term data element refers to the pieces of data, and data source refers to any system that stores a collection of data elements. Data sources are sometimes called repositories . In LDAP terms, data elements correspond closely to attribute types . Examples of data elements include a person's full name , a printer's paper capacity, or a computer's processor type. Specific instances of data elements are called data element values or just data values (for example, the full name "Babs Jensen"). In LDAP terms, data values are called attribute values .

Note

In this chapter we use less specific, non-LDAP terms such as data element so that we can direct all our attention to the issues surrounding the data itself. When we tackle schema design in Chapter 8, we will return to using the LDAP terms as we focus on how data elements are mapped specifically onto the LDAP information model.

Within your organization, data probably is stored in many places. For example, the Personnel or Human Resources department may manage a data source that includes information about all people at the company who receive a paycheck. Such information is typically managed with human resources management software, which typically stores data in a relational database management system (RDBMS).

Of course, a directory service is also a data source. Figure 7.1 shows how data sources, data elements, and data values are related.

Figure 7.1. Data Sources, Data Elements, and Data Values

One important question you will need to answer is, How does the data stored in the LDAP directory service relate to the data held in the other important data sources within my organization? To answer, you will want to learn as much as you can about the other data sources that exist within your organization.