We like to sum up the advantages of data modeling in a simple phrase: You can’t manage what you can’t see. In other words, you have to know what data you have, the rules that govern it, and how it relates to everything else in order to see value from that data. This means 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’re one step closer to ensuring the right information is used, understood and trusted across your entire enterprise. This understanding and trust in your data unlocks a host of tangible, measurable benefits, including:
Enterprise data models provide a detailed understanding of how a business operates and the data that drives these operations. These models give you the vision and insight needed to carry out large scale optimizations or changes by standardizing and document the underlying data. At the enterprise level, it’s nearly impossible to optimize a specific business function or process without a foundational model that depicts relevant data assets and their interrelationships.
Regulations like GDPR and CCPA aren’t going anywhere. In fact, they’re much more likely to expand as we move forward. That means your organization needs to adhere to them right now – while also maintaining the flexibility to support future expansions. Data models support this flexibility by governing data modeling teams, processes, portfolios and lifecycle.
Data modeling acts as a type of documentation for both IT teams and business stakeholders. When disparate roles are speaking in the same language and sharing the same understanding, it becomes much easier to simplify collaboration and improve alignment on key business functions. In turn, this simplicity and alignment unlocks employee self-service, giving them the confidence they need to use data assets to the fullest extent.
When everyone in an enterprise can see the big picture painted by data models, it becomes much easier to identify key opportunities, challenges and potential blind spots for the business. Data models make this possible by introducing a cohesive approach to data capability and literacy. If all employees are capable of using and understanding data in an aligned manner, then everyone feels a shared sense of accountability when it comes to maximizing the quality and impact of that data.
As enterprises grow, that growth is often accompanied by a ballooning network of disparate data sources and systems that don’t communicate with each other. Data modeling can uncover the relationships between these sources to eliminate redundancies, resolve discrepancies, and help siloed systems speak to each other. That means you can design, standardize and deploy high-quality data sources that span these systems while also visually comparing, analyzing and synchronizing data models with deployed data assets.
Data modeling allows organizations to spell out specific details and requirements for both the overall network of connected databases as well as the design of individual databases. With a clear visual overview, it’s much easier to identify any gaps or opportunities before the blueprints go into development. When your databases are optimized, the critical business applications that rely on them are also enhanced.