Apache Hadoop is a java based open source software framework that makes use of a network of computers for storing and processing massive amounts of data sets. All the modules in Hadoop are designed in such a way, that the framework automatically handles any hardware failure and yet continues to work. It helps you store and process data without purchasing any new and expensive hardware. Let’s take a look at some of the real-world use cases of Hadoop.
1. Financial Services:
Financial institutions need to improve their efficiency in detecting frauds more quickly and accurately. Hadoop is used by finance companies to assess risk and analyze fraud patterns. Thus you can limit the damage that a fraudster can cause to your company. Also, you can run advertising campaigns more accurately and gain valid leads.
2. Retail Shops:
Retailers make use of Hadoop to analyze structured and unstructured data of their customers for serving better. They can make use of predictive analytics to drive 73% more sales than others who do not use it. It helps them to understand more about their customers and paves a way to grow your business faster, increase profitability and win over your competitors. You could also gain insights on which of your product is liked more by the customer and rush hours in your shop.
It hard for a person to keep track of complete details about a cluster of hardware present in a company. Using Hadoop, we can generate much useful information that can be used to identify which of the machines are likely to fail soon (or) which requires immediate attention for maintenance. Thus you can easily avoid any sudden problems that might arise during the productive course at a much early stage.
Implementation of Hadoop provides huge benefits for the telecommunication companies. They can easily predict which part of the network needs maintenance within their infrastructure. It can be helpful in planning efficient network paths and recommend optimal locations for new cellular towers based on the analyzing the customer data and call drop rates.
In the case of hospitals, it is hard for a doctor to keep track of all the patient’s records and it is difficult to tell which patient is at biggest risks and need immediate attention. By using Hadoop, we can apply predictive analytics to the patient’s data collected during the past and identify who needs to be treated first. It reduces plenty of time that is wasted on minor problems and allows doctors to provide more accurate treatments to their patients.