Big Data

The government collects huge volumes of data (increasingly published as open data) and thus has major opportunities for so-called big data (analytics). In general, big data provides the opportunity of examining large and varied data sets to uncover hidden patterns, unknown correlations, customer preferences, etc. Big data encompass a mix of structured, semi-structured and unstructured data gathered formally through interactions with citizens, social media content, text from citizens’ emails and survey responses, phone call data and records, data captured by sensors connected to the Internet-of-things and so on. The notion of ‘big data’ is evolving; the variety of data being generated by organizations and the velocity at which that data is being created and updated; referred to as the 3Vs of big data. Alternative descriptions of big data add other features such as veracity, value, complexity and unstructuredness.

Big data encompasses a number of associated technologies:

Big data lakes—a ‘data lake’ is a storage repository that holds a vast amount of raw data in its native format until it is needed.

Cloud computing—the practice of using a network of remote servers hosted on the Internet to store, manage and process data, rather than a local server or a personal computer.

Unstructured data & NoSQL databases—refers to information that either does not have a pre-defined data model or is not organized in a pre-defined manner; a NoSQL database is a mechanism for storage and retrieval of data which is modelled in means other than the tabular relations used in relational databases.

Hadoop—an open source, Java-based programming framework that supports the processing and storage of extremely large data sets in a distributed computing environment.

In-memory analytics—the queries and data reside in the server’s random access memory (RAM), so increasing the speed, performance and reliability.