Abstract: Value, as the defining and most important attribute of big data is used for decision making process. Data is useless until it is not providing any valuable insight. Hence big data analytics has become a trending practice of many organizations to extract valuable information that can be further used in proactive decisions.Introduction: Everyday, huge amount of data is generated worldwide from anywhere, anytime, and anydevice. This vast amount of data creates a new era -Big data. The name Big Data had beendevised, by Roger Magoulas a researcher, to describe this singularity723-13 jan.According to a report from International Data Corporation (IDC), in 2011, the overall created and copied data volume in the world was 1.8ZB (? 1021B), which increased by nearly nine times within five years 1. This figure will double at least every other two years in the near future. Under the explosive increase of global data, the term of big data is mainly used to describe enormous datasets. bigdatasurvey 2014(15th jan). Big data is connecting three world together –physical world, human society and cyberspace. Data has been classified into two categories : data from the physical world, which is usually obtained through sensors, scientific experiments and observations (such as biological data, neural data, astronomical data, and remote sensing data), and data from the human society, which is often acquired from such sources or domains as social networks, Internet, health, finance, economics, and transportation.76 -24th jan Big data is characterized as the three V’s according to industrial data analyst Doug Laney in year 2000’s as 723-13 jan1) Volume (Data in Rest): Different types of sources are generating a large amount of data for ex. Data from sensors, data generated from commercial transactions, social media and machine-to-machine data.2) Velocity (Data in Motion): The speed at which data is arriving. Produced Data streams can arrive at different speed and should be allocated with in an appropriate manner. Different kind of IoT sensors, RFID tags and smart metering are driving the necessity to deal with data flows in real time.3) Variety (Data in Many Forms): Generated data is available in different kinds of formats such as structured, numeric data in traditional databases to unstructured text documents, email, video, audio, stock and financial transactions.But these three V’s are extended as six V’s later by adding two more V’s such as variability andVeracity and Value. They are as follows 4) Variability (Data in Highlight): Inconsistency of the data set can hamper processes to handle andmanage it.5) Veracity (Data in Doubt): Refers to the messiness or trustworthiness of the data. The quality of captured data can vary greatly, affecting accurate analysis6)Value:Big Data draws big value. The value takes the form of a value chain and is created through the processes of data discovery, integration and exploitation 102trends of big data.