Why Is BIG DATA
So Important?
B
ig Data is the term that explains the large volume of both stable and unstable data that inundates the business on a daily basis. In order to qualify as such, the data involved must exhibit categories known as the four V’s: By Matthew Meehan VOLUME - The amount of created data is considered vast in relation to traditional data VARIETY - Data comes from all different types of sources and is therefore also created by machines and processes as well as people VELOCITY - Data gets produced extremely fast, with this process continuing even as we sleep VERACITY - Big Data is sourced from many different places and therefore the quality and veracity of such data must be tested. This concept has existed for many years and it is understood by most organisations that capturing all data leads to significant potential value for the company. Even before Big Data became a concept in the 1950s, businesses were using basic analytics like spreadsheets and calculations to monitor developing trends and insights before developing the initial Big Data concept. While an increase in speed and efficiency was created by this concept, the time taken did not allow for anything more than future predictions. In comparison to now, trends are now instantly identifiable, allowing immediate strategic development that facilitates faster workstreams, staying agile to your environment and being constantly competitive. However, the main factor in utilising such data is also reliant on understanding why Big Data is actually so important for businesses in the first
66 europeanbusinessmagazine.com
place, especially considering it is not actually the amount that matters, but instead what the organisations do with it. The importance of such can mainly be understood by the development of three core categories that have been decided over time to give the greatest overview of the inherent benefits of Big Data.
Cost Reduction The reduction of cost is achieved by the new technological developments of Big Data, such as cloudbased analytics and the reduction in necessary hardware, meaning that there are significant cost advantages when it comes to both the ability and expense involved in storing large quantities of data. The ability to now take information into a more digital storage mechanism has allowed for large improvements into data driven processes such as quality standardisation and general testing. This is due to their needs for constant access to numerous complex sets of data that are especially important in industries where mistakes are critical, such as pharmacological investigation, technology and national defence. Big data is able to formulate in-depth insight that provides detailed feedback and the storage of identified issues that inform the process of assessing variables. This allows much quicker, clearer and well-informed decisions for all affected industries.
Improved Decision Making Due to the greatly advanced speeds of the data mining processes and the memorisation of analytical data, this allows new sources of information to
be speedily investigated, so that all businesses immediately understand both the state of competitors and the overall condition of their industries. This equips them with the tools to make constantly evolving decisionsdue to the speed in which these companies can now learn and internalise this information. This also allows for much further future projection, as the accuracy and consistency allows businesses to create their own agile framework which is able to handle the involved risks, while constantly updating and re-evaluating responsible memory banks in order to effectively influence every necessary decision.
