Big Data: An Introduction

Big data is high-volume, velocity and variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making. This was a definition specified by Gartner Inc in 2001 and is still relevant to this day. In simple terms, big data is larger, more complex and voluminous data sets, especially from new data sources. These large volumes of data can be used to address business problems, that would have been addressable prior.

Big data cannot be processed using traditional methods, and therefore relies upon the use of sophisticated and specific information to help optimise the information. The concept of big data has gained momentum since the early 2000’s when industry analyst Doug Laney introduced the definitions of the “3 V’s” of big data.

These are as follow:

•         Volume: This relates to the amount of data matter. Businesses collect data from a wide range of sources including business transactions, social media and videos. This data can amount to tens of terabytes but thanks to technological advancements and platforms such as Hadoop, this data can now be stored cheaply.
•          Velocity: This relates to the increased rate in which data is received, and potentially acted upon. This increased speed must be handled in a timely manner, with respect to business growth and the Internet of Things.
•          Variety: This refers to many types of data that are available. With the rise of big data, data comes in new unstructured data types. This unstructured and semi structured data e.g. text, audio etc, now requires additional processing to derive meaning and support metadata.

Big data aids businesses in a variety of ways, such as product development, predictive maintenance and customer experience. The information collected from big data allows businesses to manage operations regarding the business competitive advantage.

The end goal of big data is to transform the data it receives, into a visual element that has the ability to be understood and interpreted easily in order to improve processes, productivity and efficiency.

References:

Gartner. (2020). Big Data. [online] Available at: https://www.gartner.com/en/information-technology/glossary/big-data

Oracle.com. (2020). What Is Big Data? | Oracle Ireland. [online] Available at: https://www.oracle.com/ie/big-data/guide/what-is-big-data.html

Insights, S. and Insights, B. (2020). Big Data: What it is and why it matters. [online] Sas.com. Available at: https://www.sas.com/en_ie/insights/big-data/what-is-big-data.html