Data is one of the most important corporate assets. Of course, this is only true if this data can be found, tracked, understood, and properly leveraged. Data modeling is fundamental because it allows organizations to visualize these functions and execute the design, development, and implementation of high-quality data assets. But all too often, this value is minimized by companies that perceive it as "just" documentation or an expensive bottleneck to "the real work." Doing so is to ignore the many tangible benefits of data modeling that affect daily operations and long-term strategies.
Data modeling: data is one of the most important corporate assets.
Key advantages of enterprise data modeling
We like to summarize the advantages of data modeling in a simple phrase: you can't manage what you can't see. In other words, you need to know what data you have, the rules that govern it, and how it relates to everything else to see the value of that data. This means that data modeling is absolutely necessary as a precursor to metadata management, data governance, and data intelligence.
With an integrated view of conceptual, logical, and physical data models, you are one step closer to ensuring that the right information is used, understood, and trusted across your enterprise. This understanding and trust in your data unlocks a host of tangible and measurable benefits, including:
Business understanding through discovery, standardization, and documentation of data sources
Enterprise data models provide a detailed understanding of how a business operates and the data that drives those operations. These models provide the vision and insight needed to perform large-scale optimizations or changes by standardizing and documenting the underlying data. At the enterprise level, it is almost impossible to optimize a specific business function or process without a foundational model that depicts relevant data assets and their interrelationships.
Stricter and more effective regulatory compliance – for now and later
Regulations like GDPR and CCPA are not going anywhere. In fact, they are much more likely to expand as we move forward. This means your organization needs to adhere to them now, while also maintaining the flexibility to support future expansions. Data models support this flexibility by governing data modeling teams, processes, portfolios, and lifecycles.
Faster paths to knowledge transfer and employee self-service
Data modeling acts as a type of documentation for both IT teams and business stakeholders. When different roles speak the same language and share the same understanding, it becomes much easier to streamline collaboration and improve alignment across key business functions. In turn, this simplicity and alignment unlock employee self-service, giving them the confidence they need to use data assets to their fullest.
Better business intelligence through data capability, literacy, and accountability
When everyone in a company can see the big picture drawn by data models, it becomes much easier to identify key opportunities, challenges, and potential pain points for the business. Data models make this possible by introducing a cohesive approach to data capability and literacy. If all employees are able to use and understand data input in an aligned manner, everyone will feel a shared sense of responsibility when it comes to maximizing the quality and impact of that data.
Coherent integrations of existing information systems
As companies grow, this growth is often accompanied by a web of disparate data sources and systems that do not communicate with each other. Data modeling can reveal the relationships between these sources to eliminate redundancies, resolve discrepancies, and help siloed systems talk to each other. This means you can design, standardize, and implement high-quality data sources that span these systems, while also visually comparing, analyzing, and synchronizing data models with deployed data assets.
Advanced database design to better support application development
Data modeling allows organizations to detail specific requirements for the overall network of connected databases as well as for individual database design. With a clear overview, it is much easier to identify any gaps or opportunities before blueprints enter development. When your databases are optimized, the essential business applications that rely on them are also enhanced.
We like to summarize the advantages of data modeling in a simple phrase: you can't manage what you can't see.