Powering Real Estate Property Analytics with MongoDB + Spark

June 23, 2017

Speaker: Gheni Abla, Analytics Software Technical Architect, CoreLogic 
Level: 200 (Intermediate)
Track: Data Analytics

CoreLogic is a leading global property information, analytics and solutions provider. The company provides a range of analytic solutions for automated property valuation and appraisals. This presentation will cover a recent project at CoreLogic that utilized MongoDB for storing property and ownership data for over 150 million properties. MongoDB provided powerful support for storing and searching location-based property data. The MongoDB-Spark connector facilitated seamless integration between data access and the Spark-based distributed analytics processing and MongoDB’s replication capability provided high-availability across data centers. This session will cover CoreLogic’s software architecture and real-world development experiences with geospatial data and MongoDB-Spark connector.

What You Will Learn:

How CoreLogic manages and stores data for over 150 million real estate properties in MongoDB, and utilizes MongoDB's geospatial data support.

How to distribute large-scale analytics process using Spark and improve data access efficiency using the MongoDB-Spark connector.

How to utilize MongoDB replication for implementing high-availability between two geographically dispersed data centers.

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