Big Data

Big Data usually includes data sets with sizes beyond the ability of commonly used software tools to capture, manage, and process. If the data is huge and un organized, the problems to play with the data would be Big and quite challenging. Big Data talks about the challenges that processing systems face while capturing,storing, searching, sharing, transfering, analysing and visualizing a very huge data and unorganized data.

An example of big data might be petabytes (1,024 terabytes) or exabytes (1,024 petabytes) of data consisting of billions to trillions of records of millions of people -- all from different sources (e.g. Web, sales, customer contact center, social media, mobile data and so on). The data is typically loosely structured data that is often incomplete and inaccessible.
 
 

Big data is a buzzword, or catch-phrase, used to describe a massive volume of both structured and unstructured data that is so large that it's difficult to process using traditional database and software techniques. It derives mainly from BigTable paper published by Google in 2006. which has become the inspiration for countless NoSQL databases like Cassandra, HBase, and others. Hadoop in combination with these Big Data then provides the complete solution for computational intensive analytics for large amount of data in distributed environments
 
Hadoop is the core platform for structuring Big Data, and solves the problem of making it useful for analytic's purposes.

Data Analytics, Business Intelligence, Data Mining are all related terms and allow any large business to derive patterns from the customer's usage and from product sales to build market strategies. Statistical and artificial intelligence algorithms that are used as part of data mining. The next level of data mining is predictive analysis which is becoming a buzz word. Traditional data mining is based on historical data and many decisions are based more on experience rather than scientific predictive patterns. BI and Data Analytics provide insight, while Predictive Analytics provide the action 

It will give a perspective of the market scenario, understand the patterns of Sales by Geography, Products, Solutions, User base, ethinicity etc. and based on that we can modify our Marketing Strategy. Device better Solutions, launch applicable solutions in certain territories, or remove certain ones which are not used much... 

Data Analytics helps in developing Business Intelligence and adapt ourselves to changing market conditions...  

 

More on Big Data current development activity:

Tomorrow's cities: How big data is changing the world 

http://www.bigdatacompanies.com/

http://www.mckinsey.com/insights/business_technology/big_data_the_next_frontier_for_innovation

http://www.zdnet.com/blog/hinchcliffe/the-enterprise-opportunity-of-big-data-closing-the-clue-gap/1648