Big Data refers to a huge amount of structured and unstructured data, so huge that it is difficult to work with using normal database and software techniques. In most companies the amount of data is too large or moves too fast or exceeds current processing power. Big data can be analyzed to gain insights that lead to better decisions and strategic business moves. While the term “big data” is relatively new, the act of storing large amounts of information for study is quite old. Big data is associated with the three v's: Volume. We collect data from business transactions, social media, and information from sensors or machine-to-machine data. In the past, storing them would have been a problem, but new technologies like Hadoop have made it easier. Speed. Data flows flow at high speed and must be managed in a timely manner. RFID tags, sensors and smart meters are driving the need to manage torrents of data in near real-time. Variety. Data comes in all kinds of structured forms, from numeric data in traditional databases to 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 Shouldn't Be Banned"? Get an Original Essay In addition to high speeds and different data types, data streams can be highly inconsistent as periods increase. Is there something going viral on the Internet? Large data loads can be difficult to manage, and even more so for unstructured data. Complexity. Nowadays data has multiple sources, which makes it difficult to connect, match, cleanse and transform data between different systems. However, you need to connect and correlate relationships, hierarchies, and data links, otherwise your data can spiral out of control. Big Data has the potential to help companies improve operations and make faster, smarter decisions. The data comes from a variety of sources including email, mobile devices, applications, databases, servers, stock market data and financial transactions. This data, once captured, formatted, manipulated, stored, and then analyzed, can help a business gain actionable insights to increase revenue, acquire or retain customers, and improve operations. The importance of big data doesn't revolve around how much data you have, but what you do with it. You can take data from any source and analyze it to find answers that enable 1) cost reduction2) time reduction3) new product development and optimized offerings4) intelligent decision making. Big data analytics is the way of studying large and diverse data sets, i.e. big data, to discover hidden patterns, unknown correlations, market trends, customer preferences and information that can help organizations make better business decisions informed. By combining big data with high-powered analytics, you can perform tasks such as: Find the reasons for failures, problems and defects in near real-time. Creation of coupons at the point of sale based on the customer's purchasing habits. Recalculate complete risk portfolios in no time. Uncover fraudulent behavior before it impacts your organization. At scale, data analytics technologies and techniques provide a means to analyze data sets and draw conclusions about them to help organizations make informed business decisions. BI queries answer basic questions about business operations and performance. Big data analytics is a form of advanced analytics, which.