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Zillow Provides Near-Real-Time Home-Value Estimates Using Amazon Kinesis
技术
- 平台即服务 (PaaS) - 数据管理平台
适用功能
- 销售与市场营销
- 商业运营
用例
- 实时定位系统 (RTLS)
- 质量预测分析
- 远程资产管理
服务
- 云规划/设计/实施服务
- 数据科学服务
挑战
Zillow Group, the owner and operator of the largest online real-estate and home-related brands, was struggling to provide timely and accurate home valuations, known as Zestimates, for all new homes. The company's in-house machine-learning framework, which ran on-premise to process vertically scaling workloads, was unable to scale fast enough to meet the growing amount of data and the increasing complexity of machine-learning models for accurate Zestimates. The company specifically sought a distributed platform, which would enable the fast creation and execution of massively parallel machine-learning jobs. The existing technology was taking too long to compute Zestimates, sometimes more than a day, which meant that customers weren’t getting updated information fast enough.
关于客户
Zillow Group owns and operates a portfolio of the largest online real-estate and home-related brands, including the Zillow website. Tens of millions of users search Zillow daily for information about 110 million homes and apartments across the U.S. The most popular feature of the Zillow website is the Zestimate—a home-valuation tool that provides buyers and sellers with the estimated market value for a specific home. Zillow currently offers Zestimates for more than 100 million homes in the U.S., with hundreds of attributes for each property. The company uses a wide variety of public-record data—including tax assessments, sales transactions, images of homes, MLS listing data, and other information provided by homeowners—as inputs to its Zestimate algorithm.
解决方案
Zillow decided to expand its use of Amazon Web Services (AWS) to solve the scalability and performance problems it faced with the Zestimate tool. Zillow chose to run Apache Spark on Amazon Elastic MapReduce (Amazon EMR). By running Zillow’s machine-learning algorithms using Spark on Amazon EMR, Zillow can quickly create scalable Spark clusters and use Spark’s distributed processing capabilities to process large data sets in near real time, create features, and train and score millions of machine learning models. Zillow uses Amazon Kinesis Streams to ingest a variety of data, including public-property records, home tax assessments, sales transactions, images and video, MLS-listing data, and user-provided information. All this data is ingested and pushed into Spark on Amazon EMR, which runs machine-learning models and gives users near-real-time Zestimates.
运营影响
数量效益
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