Big Data refers to a massive amount of data both structured and unstructured, so huge that it is difficult to work on it using normal database techniques and software. In most businesses, the amount of data is too large or moves too quickly or exceeds current processing power. Big data can be analyzed to gain insights that lead to better decisions and strategic business developments. Although the term "big data" is relatively new, the act of storing large amounts of information for possible study is quite old. Big Data is associated with the three Vs: Volume. We collect data from commercial transactions, social media, and information from sensors or machine-to-machine data. In the past, storage would have been an issue, but new technologies like Hadoop have made it easy. Speed. Data flows travel at high speed and must be processed as quickly as possible. RFID tags, sensors and smart meters require processing torrents of data in near real time. Variety. Data comes in all types of forms: structured data, digital data in traditional databases, unstructured text documents, email, video, audio, stock market data and financial transactions. And two other factors: Variability. Say no to plagiarism. Get a tailor-made essay on “Why Violent Video Games Should Not Be Banned”? Get an original essay In addition to high speeds and different data types, data streams can be very inconsistent with increases in periods. Does something go viral on the Internet? High data loads can be difficult to manage, and even more difficult for unstructured data. Complexity. Today, data comes from multiple sources, making it difficult to link, match, clean and transform data across different systems. But it is necessary to connect and correlate relationships, hierarchies and data links, otherwise your data can spiral out of control. Big Data has the potential to help businesses improve operations and make faster, smarter decisions. Data comes from a number of sources, including emails, mobile devices, applications, databases, servers, stock data and financial transactions. This data, once captured, formatted, manipulated, stored and then analyzed, can help a business obtain useful information to increase revenue, attract or retain customers and improve operations. The importance of Big Data is not about how much data you have, but what you do with it. You can extract data from any source and analyze it to find answers that enable 1) cost reductions 2) time reductions 3) new product development and optimized offerings 4) intelligent decision making . Big data analytics is the means of studying large and varied data sets (i.e. big data) to discover hidden patterns, unknown correlations, market trends, customer preferences and information that can help organizations make more informed business decisions. When you combine big data with powerful analytics, you can perform tasks like: Find the reasons for outages, issues, and defects in near real-time. Creation of point-of-sale coupons.