Top data modeling solutions enable organizations to discover, design, visualize, standardize and deploy high-quality data assets through an intuitive GUI. With the ability to view “any data” from “anywhere” for consistency, clarity and artifact reuse across large-scale data integration, master data management, big data and business intelligence/analytics initiatives, today, data modeling is a critical component to many initiatives.
“Data modelers must look at the big picture of an organization’s data ecosystem to ensure additions and changes fit in properly,” explains DBTA columnist Todd Schraml, “Simultaneously, each data modeler must be focused on the minute details, adhering to naming standards, domain rules, data type practices, still remaining ever vigilant for instilling consistency across everything they do. And, while focused on all of the above, their efforts must culminate in a practical model that serves the individual project’s requirements while also being implementable, maintainable, and extensible.”
Data modeling tools can help organizations create high quality data models that enable them to shape, organize, and standardize data infrastructure, change structures, and produce detail documentation. Moreover, data modeling solutions can also help companies visualize and manage business data across platforms and extend that data to users with varying job roles and skill levels across geographies and time zones.
Increasingly, data modeling products offer a range of important capabilities such as approaches for comparing models and synchronizing them, reverse- and forward- engineering them, and offering visual interfaces for improved ease of use.
Data modeling products can also provide ways for data assets to be visually documented and reused and offer native support for new and emerging database platforms.
Many data modeling solutions also provide features to help users map and understand their information architecture to prepare for technology upgrades and process improvements as well as understand the impact of changes before they are implemented for better appreciation of risks and other challenges.
Commenting on the important of data modeling done well, Schraml notes, “Too many IT shops today think of completed projects as one-and-done efforts; and for tiny solutions, that may be fine. These solutions will live their short lives and simply be replaced in whole, later.”
While a “data Nirvana,” where database models are perfect, is not a realistic goal, it nonetheless is possible to establish an environment where data models are good enough for now, and where things are not only allowed to grow, but also are expected to evolve and change so they can continue to be good enough as the future unfolds, writes Schraml.
Best Data Modeling Solutionerwin Data Modeler
Winners' Circle by Adam Famularo, CEO of erwin, Inc.erwin Data Modeler
Businesses today are collecting more data than ever. However, you can’t manage what you can’t see. And you can’t use what you can’t understand. erwin Data Modeler (DM) is where business and data meet—and remains the gold standard for data modeling. Read on.
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