Have you ever considered making all business processes with data rules, structure, and technical implementation a bit easier? You may ask, “how?” Well, this is exactly what data modeling exists for. It’s a kind of synergy that helps to organize your data, compel it with your business needs and most importantly, makes data understandable for everyone.
What is Data Modeling?
Perhaps at first glance, data modeling may seem like something tough to understand for those who are faced with this concept for the first time. To simplify it: data modeling consists of collecting data and creating a visual representation of the whole information system or its parts to show an association between them.
The main goal of the data modeling process is to illustrate the data types, to show their structure or the way they can be grouped, and clarify their requirements. Moreover, data modeling is a very important stage when it comes to the design process, architecture, and strategy of any business-critical IT system. The systematization of schemas and formal techniques leads to a common, understandable, and predictable way of defining and managing data in your enterprise.
To get a better understanding of what data modeling is, we have to dig deeper into its types, the benefits from using and the pitfalls of data modeling itself.
Types of data modeling
There are three of the most common data modeling types (of course there are many other approaches of data modeling though):
Physical Data Modeling.
It consists of relational data objects (tables, columns) and their association. It provides a schema of how the necessary data will be stored in the database. This type of data shows the final design and illustrates the relationship between each entity.
Conceptual Data Modeling.
First, conceptual data modeling results from business requirements and needs. Its goal is to define the core business needs and make a plan on how the crucial data units relate to one another. Besides that, this type of model is the simplest one.
Logical Data Modeling.
The logical data modeling essence lies in understanding how each piece of data works with each function or how it will support the goals of your business.
Why is it not the same as data analysis? Spot the difference
Quite often, it’s confused by terms of data modeling and data analysis. However, it’s two different things that require different skill sets.
Data analysis is about what you do with the information now, how you filter the data and take out the necessary insights for your business. On the other hand, data modeling consists of creating conditions to make that data analysis possible: take the fundamental data for your business, make sure it is stored in the right place, and in the correct way.
Why should you consider data modeling in your business?
The better data modeling you have, the more business benefits you receive on the subject of productivity, efficiency, customer satisfaction, profitability, and a better understanding of your core business needs. However, you have to carefully consider the discovered data types to avoid the over-modeling issues regarding the costs and speed of development optimization.
How should you implement data modeling in your business?
Generally, the workflow of data modeling process consists of 6 main steps:
- Identify the business objectives represented in data that should be modeled, but pay particular attention to avoid over-modeling.
- Establish key properties for each business objective to distinguish them in the data model.
- Install the relationships between unites to show their connection.
- Identify the various data attributes that need to be implemented in the data model.
- Connect the attributes with each objective, so the model could represent the business meaning of the data.
- Finalize and validate data model.
Equally crucial in the data modeling process is the development team who works on it. To create a quality data model, you should cooperate with an experienced IT team, which involves testers, programmers, and data engineers.
What can you achieve with this business-wise?
1. Understanding and improving business processes.
It is what we have talked about before: you can not model your data if you simply don’t know how your business operates in the context of bigger companies. To perform data modeling, you have to clearly understand your business processes and do it in ways to allow both the development team and other people to collaborate with your information.
2. Cost and time saving
Using data modeling, you can directly define key business directives, which means this approach will save your time, making fewer revisions at implementation time. Data modeling is one of the best ways to keep your data under control. It also allows better management of data retention (cost savings).
3. Improved collaboration between developers and business teams
Data modeling also helps to improve the communication between your IT team developers and non-technical teams, which is a great benefit. Moreover, it takes part Using a data modeling system can be understandable for both sides (even for those who are not technically savvy), but at the same time still involves enough data details to create data structures.
4. Less application and data errors.
While using data modeling, you have to establish its concept from the beginning to avoid failures such as architecture bags that are pretty much expensive to remove. As a result, such an approach helps to start the application development process with a clear vision. Without question, it doesn’t eliminate the possibility of errors written in a code by developers, but it can prevent the risk of making tough errors that are hard to resolve.
Why should you consider Idego teams?
Despite the great benefits that data modeling gives, it still requires a lot of effort and expertise to build a good data model, compelling it with your business needs. Idego’s development team has valuable experience for 11 years, as well as working remotely. We can advise you on how to implement data modeling in your business to get the best out of it. Our experienced remote developers are ready to join your project under the full control of your company at every stage, bringing value to your business.