Big Data is an often-unnoticed innovation that is used throughout global commerce.

“The ability to collect data is improving all the time, but what exactly is big data?
How are businesses collecting and utilizing data to improve decision making?”

Big Data is a term used to describe data that is so large and complex that it’s impossible to process by humans using traditional data curation methods. We have been collecting, accessing and interrogating data for a long time, but the concept of big data gained momentum in the early 2000s when computational power started improving at scale.

It is an integral part of running a successful organisation and isn’t necessarily reliant on the amount of data you have at your disposal. The most important factor is how you choose to manage and interact with it. Some practical applications of big data include identifying cost reductions, time reductions, aiding with new product development and discovering new service offerings.

Overall big data, well managed, maintained and interrogated enables smart decision          making. When you combine big data with high-powered analytics, you can accomplish          business-related tasks such as:

  • Determining root causes of failures, issues and defects in near-real time
  • Generating offers at the point of sale based on the customer’s buying habits to improve conversion rates
  • Recalculating entire risk portfolios in minutes
  • Detecting fraudulent behavior before it affects your organisation

Data is often perceived to be alphanumeric, but that’s not always the case. Disruptive camera technology and image rendering is now able to monitor a prospect’s eye movements and pupil dilation to assess how people respond to visual cues. Bio-metric data used in healthcare is able to measure pulse rate and blood pressure to better predict outcomes and the fitness industry is using movement tracking to redefine recovery rates from surgical procedures.

From a marketing perspective, getting real time information on the interest shown in a promotion or headline provides a new level of enhanced insight. Imagine the opportunity of adjusting a price or promotion to suit the customer at the point of sale as a result of biometric data tracking the interest being shown in a particular product. From a healthcare perspective, imagine having all of the information you need to make better informed decisions when treating your patients.

These examples of big data are generally B2C focused, such as encouraging people to try a new brand of cereal or to watch a new genre of film, but big data also provides a real opportunity to counteract serious dangers to the security of society.

Real-time cyber-attack prediction & mitigation is a phenomenon that every government and large organisation is taking very seriously. In an ever connected world, high-tech crimes including cyber-based terrorism, espionage, computer intrusions, and major cyber fraud are problems that pose a real threat to online safety. Big data is allowing analysis of network traffic, which enables organisations to discover threats earlier and react in real time.

The ability to analyse email, VOIP, smart device geographical location and call details, and social media activity are already helping cyber security organisations better detect criminal threats and gather criminal evidence. Instead of waiting for a crime to be committed, the aim will be to prevent it from happening in the first place.

So what other real-world problems are being aided by big data?

1) Risk management

  • Being able to foresee a potential risk and mitigating it before it occurs is critical and big data has contributed greatly to the development of risk management solutions.
  • Companies are building their own tools that allow businesses to quantify and model risks that they face every day. Considering the increasing availability and diversity of statistics, big data analytics has a huge potential for enhancing the quality of risk management models. UOB is a great example of a high-risk industry mitigating risk through utilizing big data.
  • Being a financial institution, there is potential for incurring losses if risk management is not at the forefront of everything they do. The big data risk management system built by UOB enables the bank to reduce the calculation time of the value at risk from 18 hours, to a few minutes, by relying on AI to process and model large data sets and conduct trends analysis.

2) Increase marketing performance

  • Businesses have traditionally spent millions of dollars on blanket advertising campaigns, with the goal of casting a very wide net and potentially attracting a few new customers. But with custom big data tools, the marketing and advertising sector is able to make a more sophisticated analysis, leading to better decision making.
  • This involves observing online activity, monitoring point of sale transactions and ensuring ad hoc detection of dynamic changes in customer trends. Netflix is a good example of a big brand that uses big data analytics for targeted advertising. With over 100 million subscribers, the company collects huge amounts of customer data.
  • If you are a subscriber, you are familiar as to how they send you suggestions of the next movie you should watch, citing ‘based on your browsing behavior’. Using predictive trend analysis, Netflix is also moving towards commissioning new television shows and movies based on existing customer viewing behavior.

3) Drive innovation and product development

  • Another huge advantage of big data is the ability to help companies innovate and redevelop their products / service offerings. Big data has become an avenue for creating additional revenue streams through enabling innovations and product improvements.
  • Every design process has to begin with establishing what exactly fits the customers. There are various channels through which an organisation can study customer needs, before identifying the best approach to capitalize on. Once data is gathered, analysis is conducted and logical reasoning is applied before an action plan is devised.
  • The rise of Amazon Pantry and Amazon Foods is a great example of using big data to drive innovation. Amazon leverages big data analytics to move into a well-established, but outside of their core remit large market. The data-driven logistics gives Amazon the required expertise to enable creation and achievement of greater value. Focusing on big data analytics, Amazon foods is able to understand how customers buy groceries and how suppliers interact with the grocer to optimize the entire process, from supply direct to the customer.

There is no doubt that Big Data is going to play a very large part in our future and the future of all businesses. More organisations are storing, processing and extracting value from data of all forms and sizes and one issue that arises from this is that we need more innovative systems to support the collection and curation of large volumes of both structured and unstructured data.

The market will demand platforms that help data custodians govern and secure big data while empowering end users to analyse that data. These systems will mature to operate well inside of enterprise IT systems and standards.