Data Modeling is the definition of data into practice that requires a bit more work. To bridge the gap between data modeling and data integration requires a way to turn written structure into actionable code.
With the right data modeling strategy, you can gain complete control over data definition and metadata. Regarding this, in this article, we will discuss in more detail and complete what is meant by data modeling.
What is Data Modeling ?
So, data modeling (data modeling) is the process of generating a descriptive schema, the relationship between various types of information to be stored in the database.
One of the goals of data modeling is to create the most efficient method of storing information while providing comprehensive access and reporting.
Data modeling is also an important skill for scientists, whether you are doing research design or designing repository data
Your ability to think clearly and systematically about the main data points to be stored and retrieved, and how they should be grouped and linked, will be very important in the data modeling process.
Functions of Data Modeling
After we know what data modeling means, now we also need to know what the main function of data modeling is.
Previously, please note that the data model provides an intuitive diagram of data processing so that it has full visibility on the data architecture or better known as the data architecture.
It reduces many of the existing and possible risks when you get an overview of all your data, no more buried and scattered transformations, metadata, or filters.
Also make sure that all data objects required by the database are accurately represented. Omitting data can lead to incorrect report generation and incorrect results.
Using this model, it will be able to assist you in designing databases at conceptual, physical, and logical levels.
Structural modeling and data modeling can also help you define relational tables, primary keys, and stored procedures. This will later provide a clear picture of the underlying data and can be used by database developers in creating a physical database.
Data modeling is also useful for identifying missing data. Although the initial creation of data modeling takes time and effort in the long run. It makes upgrading and maintaining your iInformation technology infrastructure more practical and faster to operate.
Then, for data modeling or data modeling functions it must be done alone. This can make complex and highly technical parts of the business more accessible staff to less technical
Types of Data Modeling
The data modeling thus reveals data and relationships that provide the basis for understanding business processes by improving them. There are three types of data modeling that we need to know based on the level, namely.
The first type is Conceptual. This type of data model defines high-level user view data. These models are typically created by business and data architecture stakeholders. Its purpose is to organize, extend, and define business concepts and rules.
Next is the logical , where in this model we can determine how the system should be implemented regardless of the DBMS (Database Management System).
These models are usually created by data architects and business analysts. The aim is to develop a technical mapping of regulations and data structures.
The last type of model is Physical. This chapter will explain how the system will be implemented using a particular DBMS system.
These models are usually created by DBAs (Database administrators) and developers. The goal is to implement database an effective
Benefits of Data Modeling
In discussing what data modeling is, data models and their purposes and functions, of course we also have to know what are the benefits of data modeling
. In addition to the benefits, please note that in data modeling, there are two types of basic rules to maintain data integrity, namely entity integrity and referential data integrity.
When talking to customers about improving their data, data integrity is an important prerequisite. Before companies can start using their data to make decisions, they must be able to trust that the data set is accurate and reliable.
Here are the benefits associated with using data modeling, especially for organizations and companies that you should know about:
- Develop high-quality software.
- Reduce costs that may be incurred.
- Can achieve faster time to market.
- Clear understanding of scope, vocabulary and other developmental elements.
- Improved application and database.
- High quality documentation.
- Fewer errors or bugs in software.
- Fewer data errors in organizational systems.
- Better risk management.
This is our explanation of data modeling. So based on the complete explanation above, it can be concluded that data modeling is a process that produces a descriptive schema of the relationship between various types of information to be stored in a database.
This management issue is indeed very important in various business lines, including in the financial line. It requires proper financial management so that the company’s operations can run smoothly.