Big Data refers to technologies and initiatives that involve data that is too diverse, fast-changing or massive for conventional technologies, skills and infrastructure to address efficiently. These include a wide variety of apps such as genomics, clickstream analysis, customer Sentiment analysis, log data collection and ad technology.
Leading organizations are leveraging Big Data to:
- Build new applications that were not possible before, like the City of Chicago’s WindyGrid initiative;
- Understand customer sentiment, like Salesforce.com’s social media marketing platform.
- Reduce costs, like a Tier 1 bank saving $40M over 5 years with MongoDB; and
- Make the world a better place, like the Broad Institute’s open-source genomics platform.
- Agility. Today the marketing department wants to add Pinterest boards. Next quarter it may be a different social network. Changing the database with your application is difficult in a relational world.
- Volume. The Broad Institute started with 400 data points. In just 24 months that jumped to 1.4M. The database must support rapid growth without downtime.
- Velocity. Criteo’s online ad platform processes 1B requests and 350M updates per day. Can your database support that rate velocity?
- Variety. The City of Chicago collects data from over 30 different departments, each in a distinct format. Doing that in a single data store is hard.
- Dynamic schemas in MongoDB provide a simple way to evolve the database with your application.
- Documents in MongoDB lend themselves to combining structured and unstructured data in a single data store.
- Native analytics make it easy to deliver actionable insights in real-time.
- Horizontal Scaling allows organizations to support massive data volumes and high ingestion rates.
K Young, Mortar
Kelly Stirman, MongoDB
Mike O'Brien, MongoDB
Craig Weissman, Duetto Research