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Data Modeling and Using It to Get Out of Sticky Situations

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Monday, November 6, 2017 at 9:09 AM filed under General postings

Data modeling is a useful technique by which a process of documentation of any complex software system design is simplified to a diagram so that it can be easily understood. It uses a set of text and symbols to present the way data is flowing in the entire process. This diagram, which is easier to comprehend, can be used as a blueprint for construction of new software as well as for re-engineering a legacy application. It makes complex processes quite easy to grasp and implement, thereby also making it quite easier to pinpoint any mistakes in the system.

Business analysts use data modeling techniques to solve some of their most tricky and sticky project challenges. Even though data models might look very complex and intimidating at the first glance, it is easier to comprehend them if you take a look and analyses different levels of abstraction.

There are a number of different approaches to data modeling. Here are the commonly used types.

Conceptual Model

It is used for representing business concepts and ideas only. It does not take into consideration the technical design in question; therefore, the conceptual model falls under the umbrella of what a business wants.

Enterprise Data Modeling

Enterprise Data Modeling is similar in essence as well process to conceptual data modeling. But it is unique in the sense that it addresses the unique requirements of the specific business.

Logical Models

It is used for making sure that the business concepts are theoretically implementable in a database design although still it might not include all the details of the physical database structure. Therefore, logical model falls in the intersection of what the business actually wants and how the solution team has to implement it.

Physical Models

This model specifies the actual database tables and fields which have been created as part of the database. The physical model falls under the umbrella of the process of designing and implementation of the database.

Any of the data modeling techniques can easily be completed at various different levels of abstraction. At the end of the day, for any business analyst, the most important task is to ensure that the business perspective actually informs the critical technical decisions.

Here are some of the tools and techniques that will help you implement your data modeling without any kinks in the way

Entity Relationship Diagram

It is a tool which helps you to visualize the relationships between the key business concepts in order to encourage the database designs focused particularly on the business.

Data Dictionary

It is a spreadsheet format which helps you to communicate with business stakeholders clearly, in an organized fashion. Thus, it eliminates all the huge lists of fields inside use cases or any other requirements document.

Glossary

It is important to clarify your requirements document besides encouraging effective communication among stakeholders. Thus, the glossary helps you learn about a new business domain. It also makes the rest of the data modeling techniques much easier, giving you an unambiguous and much clearer collection of terms to work with.

Data Mapping

Data mapping process in its simplest term is to map source data fields to their related target data fields. For example, the value of let’s say a source data field A goes into a target data field X. Data Mapping tools allow developers to code these conversion rules to achieve the expected target output.

With the use of data modeling techniques, one helps a business make better data requirements related decisions and helps to smoothen out all the technical design process.

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