What is Big Data ?
Big Data is a term that describes the large volume of data – both structured and unstructured – that inundates a business on a day-to-day basis. But it’s not the amount of data that’s important. It’s what organizations do with the data that matters. Big data can be analyzed for insights that lead to better decisions and strategic business moves.
Big data’s big potential
The amount of data that’s being created and stored on a global level is almost inconceivable, and it just keeps growing. That means there’s even more potential to glean key insights from business information – yet only a small percentage of data is actually analyzed. What does that mean for businesses? How can they make better use of the raw information that flows into their organizations every day?
Big Data History and Considerations

Volume
Velocity
Variety
Benefits of Big Data
Using the information kept in the social network like Facebook, the marketing agencies are learning about the response for their campaigns, promotions, and other advertising mediums.
Using the information in the social media like preferences and product perception of their consumers, product companies and retail organizations are planning their production.
Using the data regarding the previous medical history of patients, hospitals are providing better and quick service.
Big Data Cloud Hosting with Hadoop Computing
Hadoop is an open-source software framework for storing data and running applications on clusters of commodity hardware. It provides massive storage for any kind of data, enormous processing power and the ability to handle virtually limitless concurrent tasks or jobs.
Hadoop delegates tasks across these servers (called “worker nodes” or “slave nodes”), essentially harnessing the power of each device and running them together simultaneously. This is what allows massive amounts of data to be analyzed: splitting the tasks across different locations in this manner allows bigger jobs to be completed faster. There are two key functional components within this ecosystem: The storage of data (Hadoop Distributed File System, or HDFS) and the framework for running parallel computations on this data (MapReduce).