There is hardly any resource that is more important to the strategy and success of a business than data. With simple inferences drawn from this data, such as what kind of products a part of consumers buy, firms can tune their approach for better business decisions. But there is data, and there is big data! Improvements in computing have resulted in an increase in the data available to companies. There has been an explosion in the amount of data that is generated every day. While spreadsheets and nicely coded files allow companies to keep a realistic amount of data, the computing ability to gather, store and consolidate data on a large scale meant that information could be available at the click of a button. What is Big Data? What is Big Data The concept of Big Data is not new. It dates back to 2000, where it was described in terms of its huge volume, the extremely high velocity with which it is created and the diversity of sources that create and share this data. The variety of data comes in two categories: structured, and unstructured. Structured means that the data is carefully labeled and categorized. For example, it could be high amounts of data showing how many Google users search a particular term in a day. On the other hand, unstructured data is data that is documented without much intent or purpose. It is often recorded without being in any dynamic use. Such data is therefore, not neatly tagged or categorized. This type comes in a number of varieties—text, video, and images. Unstructured data is random, enormous and difficult to analyze. The volume of Big Data overwhelms the normal data warehouse. For instance, Facebook reports that its users register 2.7 billion comments and likes per day. For many, this extent of data is nerve-racking—they cannot keep up with it, sort it, analyze it and extract value from it. It can be challenging to manage data when it flows at a velocity that many players cannot handle. For Big Data to be a useful, it must be analyzed at a rate that matches the intense speed at which information enters data warehouses. The idea behind Big Data and any type of data is: the more you know, the more you can do. Simply put, information is power and in the modern world we are in, power is dynamically measured by how much one knows and can act on. By gaining access to growing amounts of data and relating more data points, it is possible to identify connections that were previously concealed and harness powerful insights from them. Big Data projects use quality analytics that influence machine learning and artificial intelligence to hitch the potential insights. The process of tapping the value in this data is done in three steps: Sourcing data The first step is sourcing data from several applications and places. Basically, traditional means of data integration cannot handle [...]