Big Data, Analytics and Hadoop

 Three of the biggest catch terms in technology today are Big Data, Hadoop and Analytics.  Often times, they are used interchangeably, when in reality they are three unique capabilities and categories.  Each solves a different, but related, set of struggles within IT and the businesses that leverage IT for unique advantages.

Start with Big Data.  Big Data is a term we hear more and more often about the developing struggles at many companies to cope with growing volumes of data and changing varieties of data.  There is no mark that says where Big Data begins, but is rather a dramatic change for an organization that requires them to look at new tools, technology, processes and skill sets to address the challenges they face.  Big Data is focused on the efficient storage, movement and organization of these evolving data types.

Analytics is related to Big Data, but has some variations.  Where as Big Data focuses on the data itself and the infrastructure to manage the data, Analytics is about putting that data to use and enhancing the capabilities of an organization.  Analytics is about taking that data and ensuring that actionable information comes from it that the company can execute on.

Finally, Hadoop, one of the most common technologies being talked about today.  Hadoop is a technology that can be used to enable organizations to manage their Big Data, while building a platform for more advanced analytic capabilities.  Hadoop is a rapidly growing open source project that has been adopted by many main stream organizations as a standard method for the storage and processing of complex data sets.  Hadoop is one of many tools that you can use to enable Big Data and begin to implement an Analytics strategy.