Why Do Enterprises Need Data Modeling?
Put simply, organizations rely on data modeling to see a clear picture of their data and get the most impact from it in an organized, easy-to-visualize manner. This in turn supports better decisions, drives more robust application development, helps the organization stay compliant with data regulations, and powers innovation. Enterprises that want to advance artificial intelligence (AI) initiatives, for instance, won’t get very far without quality data and well-defined data models.
For decades, data modeling has been used to define, categorize and standardize data, so it can be leveraged by information systems. This is more important than ever in a modern data landscape, where data can be structured or unstructured and can exist on premise or in the cloud. In the face of massive volumes of data, automatically generating data models and database designs is a cost-effective way to increase efficiency and reduce errors while raising productivity across the board.
Of course, different organizations have different needs. For some, the legacy approach to databases meets the needs of their current data strategy and maturity level. For others, the greater flexibility offered by NoSQL databases makes NoSQL databases – and by extension, NoSQL data modeling – a necessity. Bringing data to the business and making it easy to access and understand increases the value of data assets, providing a return on investment and a return on opportunity. But neither would be possible without data modeling providing the backbone for metadata management and proper data governance.