Enterprise data modeling refers to the pursuit of developing a single view of data across an enterprise, agnostic of any system or application. Many organizations suffer having their data in silos across dozens of systems without an easy way to connect and leverage that critical information.
This goal to establish an enterprise-wide data model is ever elusive for many organizations working with traditional relational databases. But the payoff to creating a single view of data is immeasurable.
Consider the example of retail. Imagine how an online retailer could leverage customer purchase history with real-time inventory data. The chances for making that sale would be greatly increased because the retailer is able to connect the data points and to serve up tailored offers to customers based on their interests.
Developing that single view of data is where many companies have stumbled however. This is where MongoDB can help. As a newer generation database that offers a flexible data model, MongoDB lets you easily integrate your data across the enterprise and all for less money than the typical traditional database technologies.
Take the real-life example of MetLife. The insurance giant wanted to create an integrated view of its data across 70+ disparate systems to provide better, more personalized service to over 100 million customers. For years they tried unsuccessfully to do this using relational database technology.
By enlisting, MongoDB, however, they were able to build a prototype of a new system, dubbed “The Wall,” within two weeks. In just three months, MetLife was able go live with a new call center system that integrated these disparate systems to provide a superior customer service experience for all of its customers.
Want to hear more about how MongoDB has helped organizations pursue an enterprise data model with great success? Download our free white paper.