Your data is your lifeblood. Too bad it’s strewn across your organization, locked in siloed systems. Hordes of companies have tried to build the elusive single view. Most have failed.
With MongoDB, you can build a single view of anything. Faster. With less money.
Firm-wide view of exposure across asset classes, counterparties, and geographies to manage current risk, and anticipate opportunities.
Single view of military assets – fleets of tanks, ships, Humvees – to better understand how they’re used and where to deploy them next.
Single view of the user across products and logins to know what they’re buying, how they’re interacting with the technology, and what they want.
Omni-channel in a single view, from real-time inventory to historical customer behavior, to create a seamless, branded experience.
|Single View is Hard||MongoDB Makes it Easy|
No Solution. Trying to consolidate different data in different formats from different systems in a relational database is hard and in many cases impossible.
Elegant Solution. MongoDB can incorporate any type of data, no matter what it looks like or where it comes from, while providing all the features needed to build a powerful application.
Stalled. Relational databases render teams of architects, developers, and DBAs powerless to iterate and be agile. Instead, they wrestle with data ingestion, transformation, and schema problems for months or even years.
Ahead of Schedule. Your teams move faster with MongoDB because its dynamic schemas let them iterate. They spend less time prepping data for the database, and more time pushing the project forward.
$$$$. Large teams tied up for long periods of time make these projects expensive. Proprietary software and hardware add to the cost. The business case becomes hard for you to justify.
MongoDB Query Language. MongoDB's expressive query language, indexing, and aggregation capabilities make it possible to find, filter the data, no matter how the business needs to access it.
Different systems from different departments with different types of data don’t communicate with each other. Bringing them together to create a single view is hard.
Diverse Data Types. Reconciling the schemas of data from different systems is hard and in many cases impossible. Relational databases weren’t built for this.
Rigid Schemas. You need the ability to iterate on your schema. Today you’re pulling in data from legacy customer service systems. Tomorrow you may need to incorporate customer sentiment analysis. Evolving relational databases at this pace is not easy.
Feature Trade-offs. A Single View application is only as good as its ability to serve up fine-grained access to the data within it. You can’t sacrifice data access capabilities – like ad hoc queries, secondary indexes, and the ability to aggregate data – for flexibility.
Documents. Using MongoDB’s document model, you can incorporate any type of data, no matter what it looks like or where it comes from. JSON documents support all the basic data types you’d expect (e.g., numbers, strings, binary data, arrays) without requiring you to define or enforce a schema.
Dynamic Schemas. Schemas in MongoDB are self-describing. Iterate on the schema without having to rethink it entirely. Pull in new data when you need to. MongoDB documents can also vary in structure, which means documents from one system don’t need to have all the same fields as documents from another.
MongoDB’s expressive query language, indexing, and aggregation capabilities make it possible to find and filter the data, no matter how the business needs to access it.