In integration, data modeling is crucial. However, it is often misunderstood and downplayed.
This post explores the role of data modeling in data integration and how it can act as a bridge between business processes and IT processes in the enterprise. Read on to learn more.
What Is Data Integration?
Before launching a discussion of what data modeling is, it makes sense to establish a definition for data integration a highly misunderstood term.
Remedi defines data integration as “the collection and integration of electronic transactions, messages, and data from internal and external systems and devices to a separate data structure for purposes of cleansing, organizing, and analyzing the joined data.”
Data integration takes place in data warehouses. You need specialized software to host large data repositories from internal and external sources. When performing data integration, the software extracts, amalgamates, and then presents the information in a unified form.
What Is Data Modeling?
A data model is a common reference nexus for business and technical rules. It provides an inventory of the information sets upon which the organization operates, and clarification of critical terminology and a definition of core business rules and practices.
There are four levels of data models. They are:
At the enterprise level, the purpose of data models is to organize and scope business domain areas, while at the conceptual level, the goal is to communicate and define business rules. Logical data models are meant to clarify and detail business rules and data structures. The logical data model actually contains the business and technical data quality checkpoints for the intended data integration process. Lastly, the objectives of physical data models are the technical implementation in a database.
How Can Data Modeling Bridge Business Processes and IT Processes in the Enterprise?
Now that a definition for data modeling has been established and its objectives have been defined, it is time to explore how data modeling creates a bridge between business processes and IT processes.
Data models have value to a business because they provide a structure through which the IT department can manipulate the flow of digital information. Without a data model, you cannot clean, organize, or analyze information efficiently.
From a business perspective, a data model validates corporate requirements. You need a data model to perform day-to-day tasks, including the information analysis. A data model provides the structure and order for employees to utilize information at every level, from the front lines to the C-suite.
What happens when there is no data model? You simply cannot derive adequate value from the information you possess. As a result, you cannot make the right decisions, which has a significant and negative effect on your firm.
In today’s business world, you cannot make choices based on out-of-date or inaccurate information. You need current, correct data. A data model enables that for successful data integration. For more information about building a data model for data integration, contact us today.