You’ve probably heard the term data model when dealing with big data. Data models enable an enterprise to define and categorize its descriptors so that all its information systems can access that data. Strategic data modeling helps determine the kind of data you will need for your business while data analysis focuses on data description and categorization. For example, businesses can use Confluent Schema Registry to describe and categorize their data. Here are is how data models can benefit your business.
Data models allow you to build apps at a lower cost. In fact, data modeling takes up less than 10% of a project budget and can cut programming costs by up to 70%. It allows project managers to spot errors early enough before they get out of control. That way, you can fix a mistake before the software gets into customers hands. Financial software vendors are using data models as the nucleus when developing apps. Data models make the process of app development faster and with few errors.
Just as a general contractor needs a blueprint to construct an apartment, app developers need a data model to build apps. Premature coding is the primary source of failure of software development efforts. However, data models help an app developer to define the problem and determine the best approach to solve it.
You can estimate the complexity of the software using data models. That helps you gain insight into the level of risk and efforts involved in the project execution. What matters is the size of your data model and the intensity of its interconnected tables. An application database that has a higher inter-table connections intensity is a bit complex, and therefore, prone to more risks of failure during deployment.
Often, businesses find themselves with a variety of systems that can’t integrate. However, modeling data in each of these systems can help resolve discrepancies, spot redundancies, and integrate disparate systems. That helps improve communication and make your processes more efficient.
Data models are a form of documentation for both field technicians and business stakeholders. Data modeling helps in the development of standard vocabularies that can be shared across different job roles. The continued provision of a well-organized business glossary enhances the ability to convey and document information about your business. In fact, a well-executed data modeling can help you build a data dictionary that you can use as a training aid. Data modeling is a subject you will need to liberate in especially when dealing with big data.
Fewer Application Errors
A well-executed data model allows app developers to define concepts and resolve the confusion. While app developers can still make slight errors when coding, data models minimize the chances of making grave mistakes that are difficult to fix. For example, a highly scalable data model can help you create a system to trace supply from origin to final destination.
Analytical data mining is made possible by the documentation inherent in a data model. All you need is to load routine business data into a database and start mining it. Companies construct a database for data analysis. Data models allow an app developer to normalize and define data based on the attributes it can possess. Data modeling provides app developers with the tools they need to query and derive reports from their database. Without a data warehouse, you can find yourself with a lot of data, but with no efficient ways to leverage it. However, a data model and well-designed data warehouse can enable users to access information that perhaps they didn’t know was in existence.
Data models enable an enterprise to spot market trends and spending patterns. With a data model, it is easier to make predictions so that you can find ways to navigate challenges and opportunities. Data modeling also helps your employees to understand how your processes work and define the data that drives it. As such, you need to know how data gathered from customers can benefit your business before building a customer database.