Artificial intelligence (AI), mobile, social and the Internet of Things (IoT) are generating data complexity, new forms and sources of data. Big data analytics involves using advanced analysis techniques on very large and diverse data sets that include structured, semi-structured and unstructured data, from different sources and of different sizes, from terabyte to zettabyte . Big Data is a term applied to data sets that are larger or larger than the ability of traditional relational databases to capture, manage, and process data with low latency. And it has one or more of the following characteristics: high volume, high speed, or high variety. Big data comes from sensors, devices, video/audio, networks, log files, transactional applications, the web, and social media. Most of them are generated in real time and on a very large scale. Big data analytics allows analysts, researchers, and business users to make better and faster decisions using previously inaccessible or unusable data. Say no to plagiarism. Get a tailor-made essay on “Why violent video games should not be banned”? Get an original essay Using advanced analysis techniques such as text analysis, machine learning, predictive analytics, l Data mining, statistics and natural language processing, businesses can analyze previously untapped data sources, independent or combined with their existing business data, to gain new insights to make better and better decisions. faster. Quora and Facebook use Big Data tools to get to know you better and provide you with a feed that, in theory, you should be interested in. The fact that the stream isn't interesting should show how serious the problem is. Credit card companies analyze millions of transactions to find patterns of fraud. Maybe if you bought Pepsi with the card followed by a large purchase it could be a fraudster? Big Data describes a holistic information management strategy that includes and integrates many new types of data and data management alongside traditional data. Big Data has also been defined by the four Vs: Volume. The amount of data. Although volume indicates more data, it is the granular nature of the data that is unique. Big Data requires processing high volumes of low-density unstructured Hadoop data, i.e. data of unknown value, such as Twitter data feeds, web page and application click streams mobile, network traffic, sensor-activated equipment capturing data at high levels. the speed of light, and many more. It is the task of Big Data to convert this Hadoop data into valuable information. For some organizations this can be tens of terabytes, for others hundreds of petabytes. The rapid speed at which data is received and possibly processed. The highest speed data is normally streamed directly into memory rather than being written to disk. Some Internet of Things (IoT) applications have health and safety implications that require real-time assessment and action. Other Internet-enabled smart products operate in real or near real time. For example, consumer e-commerce applications seek to combine mobile device location and.