This video intends to be a part of a short discussion about the Few Customer case studies where hadoop can be used as a solution. We have the some case studies by which we can check the involvement of Hadoop in various sectors.
Case Study 1: Children’s Hospital Los Angles
Industry – Healthcare
The hospital is completely digitalized and every reports like scan reports, blood test and other transactions like payments, hospital management data and others are stored as a digital data, and each day, they are getting more data. The problem is that they are not aware of methods to store and manage this vast amount of data.
Collecting lots (billions) of data points from sensors / machines attached to the patients. Previously, this data was periodically purged, as storing this large volume of data on expensive storage was expensive.
Continuously streaming data from sensors/machines is collected and stored in Hadoop. HDFS provides scalable data storage at a reasonable cost.
Hadoop Cluster Size: They are using closer to 200 node clusters.
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Customer Case Study 2: China Mobile
Industry – Telecom
Problem – China Mobile Stores billions of mobile call records and provides real-time access to the call records and billing information to customers. Traditional storage/database systems was unable to scale up to the loads and provide a cost-effective solution. This issue is just not with
China Mobile alone, every telecom company are facing the same issues.
HBase is a NoSQL database, in simple words; HBase is the database of Hadoop. HBase is used for storing billions of rows of call record details. Approximately 30TB of data is added monthly.
Hadoop Cluster Size: 100+ nodes. Their Hadoop vendor is Intel.
Customer Case Study 3: Etsy
There are lot of Retail industries using Hadoop for managing huge amount of data. Let’s look at Etsy, which is one such example. Etsy is an online marketplace for handmade stuff.
Analyzing large volumes of log data, without taxing the databases.
Etsy uses Hadoop to analyze large volumes of log data to calculate user behavior, search recommendations etc. They are using Amazon Elastic Map Reduce (EMR) for this purpose.
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