In other words, data models can be compared to the building plan possessed by an architect. Data models are mostly developed using two methodologies, such as, the Object Model approach and the Entity-Relationship (ER), which in turn is mostly used to create data models for relational databases.



Additionally, creation of data models is inclusive of a multitude of steps such as identification of data objects and their relationships, drafting Entity-Relationship diagrams with relationships and entities, refining the ER diagram, adding key attributes and non key attributes to the diagram, drawing generalization hierarchies, validation of data model via normalization, and above all, incorporating integrity and business rules to the model. It is therefore important that building of data models require careful planning and analysis.

Broadly speaking, data models and data services play a pivotal role in the development of a database, as it is highly important to check whether all of the data objects pertaining to the building of the database are represented accurately and completely. In short, data models serve as a blueprint to build the database.

Further, data models employ only natural language and easily understandable notations, which in turn allows the end-users to effortlessly verify and review the database. Understanding the importance of data models and its services, nowadays many of the learning centers engage in providing world class training for developing data services and data models.

Developing data services and data models training usually last for three days. Mostly, the courses are categorized into nine sessions. In the first session, such topics as Design Processes for Business Solutions, the role of design processes in developing a systematic approach to effective solutions, and service layers and the design phases, are covered.

Included in the second session are conceptual design level data requirements for business solutions, the purpose and importance of conceptual designing, and data requirements in conceptual design. The third session is replete with topics such as Data Normalization, Purpose and Role of Normalization, and the role of keys in entity relationships. Among the topics covered in fifth session are physical data design, purpose and role of data design, and data optimization.

Data integrity, business rules for the implementation of data integrity, identification and implementation of data integrity requirements, and issues that can potentially lead to design problems, are some of the topics involved in the sixth session.

The topics discussed in seventh session, among many others, are developing data services, data services design, and info on how to select appropriate data access technologies. Significant of the topics covered in the eight session are data storage considerations, factors influencing the selection of data storage technology, and info on data storage products. Application of knowledge, review course objects, and review learning needs complete the last session.

In a snap shot, developing data services and data models training or courses covers topics such as:

- What is data model?

- What is physical data model?

- Advantages of data model

- Relational Database Terminology

- Requirements for gathering and documenting business

- How to handle complex data relationships including recursion, supertypes, and subtypes

- Determination of primary keys

- How to implement relationships with foreign keys

- Info on domain and derived attributes

- Diagramming entity relationship

- Diagramming table

- Normalization and Denormalization

Lectures, subject discussion, and team-based workshops also form part of the data services and data models training. Above all, on completion of each session, a lecture guide is given to students, which include a variety of examples as well as workshop solutions on data models.

Data model and data services training can be taken by anyone including database experts and non-technical professionals, such as, application designers, business analysts, database administrators, and developers. However, it is important that prior to joining the course, the candidate must have adequate knowledge on Developing Business Solutions and Analysis of Business Requirements.

Once the course is completed, students become well-versed in the principles and terminologies pertaining to data modeling. This in turn enables them to effortlessly handle relational database terminology. Another benefit of this course is that it allows students to easily convert business requirements to logical data models.