Groupon’s original business plan. Image source: Amanda Peyton (via The Point blog)
If you work in digital, you have met them. The data people. You know, the ones who can see level upon level of digital data unfolding in their mind’s eye? The Beautiful Mind types who have the ability to create an almost three-dimensional Excel spreadsheet? Perhaps you are one of these people, and this stuff comes naturally to you. For the rest of us non-data thinkers, creating a digital map on paper is a skill. It’s known as data modeling.
The idea of a data model is to create an overview of a digital project that all invested parties can access, understand, and use to do their jobs. Whether you are a data specialist, an agile whiz, or just a content strategist who studied James Joyce in college and doesn’t inherently think in data bytes, if you work in digital, you will probably have to create a model.
According to IBM, 90% of the world’s data was created in the last two years. In this data age, there’s an ever increasing need for tools and techniques to help analyze and store that data. Enter MongoDB, an open source, document-oriented database that was built to provide enhancements in data modeling and make data storage a breeze.
MongoDB takes a document-based approach to data modeling. This allows developers to model their data in whatever way makes sense to their application, without sacrificing anything in the ability to query their data or database performance. Compare this to relational database systems (such as MySQL and PostgreSQL), which model data in rows and columns like an Excel spreadsheet. Alas, not all data sets can conform to these strict structures.