Difference between Big data vs Hadoop
There is a lot of confusion between big data vs hadoop. Even Professionals also get confused when any one asked to define big data and Hadoop.
Big data was born out for the necessity of data sets growing so large and complex that traditional tools are no longer sufficient to process this data. By aggregating large amounts of data from different sources makes big data very powerful for business decision-making, revealing insights and behaviours faster and better.
Big data as a term has huge meaning, it can be described in diverse ways but actually big data means data so large or complex.
Big data can be either structural or unstructural. A data which can’t be stored and processed by using normal computers is called big data. For example, terabytes of data.
Big data is characterised by it’s high velocity, volume and variety of data.
Velocity: Data generated very fast. Millions of customers measured in terabytes
Volume: Source data updated daily or real-time
Variety: Different forms of data.
Sources of Big Data
- Social Networking: Face book, Twitter, Instagram, Google+ etc
- Sensors: Used in Aircraft, Cars, Industrial Machines, Space Technology, CCTV Footage etc.
- Data created from Transportation Services: Aviation, Railways, Shipping etc.
- Online Shopping Portal: Amazon, Flipcart, Snapdeal etc
- Mobile Applications: WhatsApp, Google Hangout, Hike etc.
- Data created by different Firms: Educational institutes, Banks, Hospitals, Software Companies etc.
Advantages of Big Data for the Banking Industry
Big Data can offer a number of advantages for, both banks and their customers as follows:
- Fraud detection
- Compliance and regulatory requirements
- Customer segmentation
- Personalized marketing
- Risk management
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Hadoop is impacting today’s data world. It is an open source tool, it means source code is freely available and we can change source code if any functionality doesn’t satisfy our requirements. Hadoop is a java based programming framework. It is a part of Apache project sponsored by the Apache Software Foundation. It is based on Google’s Map Reduce, a framework in which application is broken down into a large number of small parts. Its framework is using in major companies like Google, Yahoo and IBM etc. Preferred operating systems are linux and windows but it can also work with BSD and OS X. Hadoop is one of the tool used to handle big data.
Advantages of Hadoop:
- Cost effective
- Resilient to failure
The main difference between big data and hadoop
Big Data is nothing but which handles large amount of data sets. Hadoop is a single framework out of dozens of tools. Hadoop is designed to process large volumes of data. The banking and financial services industry are one of the biggest adopters of Big Data technologies such as Hadoop.