Big Data and Cloud Computing- A Better Understanding of Data and Processing for Making Insightful Data

Data is the digital footprint of a person, something or someplace. It is one of the most valuable things in today’s digital world. In recent days, there is a lot of data around us to be stored analyzed and processed. Earlier there was a time when employees used to produce data for the users. They used to fill up forms and enter the data of different users. Then in recent days, it is the end users who are producing the data through different media and ways. Every time we sign up, search on the internet, that data is collected and stored. In social networking sites, we provide information about our own voluntarily. Since the end users have started producing data, the amount has increased tremendously. Moreover, nowadays, machines are producing data in different ways. There are lots of cameras, sensors, telephone booths, atm machines, and other techs to produce data each and every second. These data can be the temperature, humidity, image or anything else. This vast amount of data and its variety can be used for different purposes.

Data processing has become faster than before, as mentioned the vast amount of data needs a lot of processing power. Earlier there was a very few amounts of data and didn’t need so much processing power. Nowadays parallel processing is used to process this huge amount of data within a very short time. The result of this analytics can be used for different purposes like health sectors, environmental warning or improvement, education, information security and almost each and every aspect of life and earth. Millions of data are captured and stored by satellites around the earth. All this data is meant for some use.

Data collected from different sources are structured, semi-structured or unstructured. The large volume of data can be stored and processed in a distributed method. The infrastructure based data warehouse and data centers have become more of infrastructure-less when it has started to move to the cloud.

As the scalability of big data has been increased, the use of cloud infrastructure and parallel processing are being used. The scalable database management system has become more flexible nowadays. The relational database management system has become more fluent than ever, moreover, the existence of NoSQL database has made the processing and storage more fluid and user-friendly. The infinite number of processing power is added to the infinite number of data generated every moment. The data has grown scalably larger in orders and magnitude and the processing power has been increasing scalable higher as well. This is the technological shift of big data and parallel processing on to it. Technologies used today like Hadoop which is used for aiding parallel processing and MapReduce which is more of a table of content on each server that is it is a snapshot or cliff note of data stored and processed in each of them.

As the processing and storage become more complex than ever, new technologies, ideas are being used in this place.


Originally published at http://techpark77.wordpress.com on July 21, 2017.

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