See also: Big data numbers
There is no commonly held definition but a general rule of thumb is that big data has to fit two of three criteria:
- Volume: large sets of data;
- Velocity: fast changing;
- Variety: structured, semi structured and unstructured data much of which is increasingly owned outside the organisation.
For example, data stored about your customers on your CRM system, is structured, while email, comments left on social media or a video’s contents are not.
Much of the time the data will be a combination of all three factors, but notably big data does not have to be big.
The real reason you should be interested in big data is that it can genuinely deliver competitive advantage.
For example, fraud is growing faster than insurance companies can fight it. It is estimated that 10 to 20 per cent of all auto insurance premiums can be attributed to fraudulent claims.
Using predictive modelling, identity search technologies and a fraud indicator rules engine, you can identify patterns and behaviours indicative of potential fraud.
Earlier identification of potential fraud can then trigger additional data collection and case management activities to uncover cases with the highest probability of fraud.
In solutions running today, up to twice as many potentially fraudulent claims are being detected, with few false positives allowing earlier investigation.
The power of big data is that we now have the technology to extract valuable business insights from a huge range of internal and external, structured and unstructured data to understand what’s happening now, and what’s likely to happen next rather than what happened in the past.
Fast and timely
Einstein said “Everything that can be counted does not necessarily count; everything that counts cannot necessarily be counted.”
The data revolution just changed that. Previously organisations focused on their most important data.
The power, intelligence and speed of the latest business technology make the era of big data a reality. It is now possible to mine huge datasets cost effectively.
The potential to improve business performance by renovating the way you do business and make decisions is exciting.
Blue Cross and Blue Shield faced the challenge of creating the world’s largest healthcare informatics data warehouse at the time.
It is a fascinating technical and business solution that shows how big data can turn into big rewards.
They formed a new company called Blue Health Intelligence whose primary mission is to monetize this Information Asset.
The solution integrates data from up to 40 member companies. It is capable of processing medical and other types of claims for 90 to 100 million people, offering the most comprehensive source of accurate healthcare research data to be found anywhere.
Blue Health Intelligence creates new collaboration opportunities for physicians, researchers and health policy makers working together with the Blue Cross and Blue Shield companies to improve the quality and consistency of care.
However, the fact organisations will be using these new insights to make important decision means they have to be sure that the way they collect, store, analyse and distribute data is optimised. And with data set to grow by 650 per cent in 5 years, this means taking action now.
If you’re shaping and executing your business strategy around the insights and predictions your systems will make, you need to know that you can trust the fidelity of the data.
You need a robust, reliable, scalable IT infrastructure that can support the volumes, velocity and variety of data and you need to imaginatively mine it to produce accurate, actionable insights faster than your competitors.
Big data goes beyond business intelligence. The predictions you make are just as likely to be needed by a sales person on the road or a customer services executive in a call centre as they are a board member.
Identifying which people, or machines in your organisation need the insight and how to get it to them at speed and securely is the difference between competitive advantage and increased operational costs.
If you applied big data solutions to your entire organisation it could take up a lot of budget and be very distracting.
Prioritisation is the way to go. There is no need to apply big data analytics and techniques to every part of the business.
Engaging the business as a partner in prioritising and exploiting the potential of big data is critical or executives could find their investment in the latest big data tools and techniques will not have the desired outcome.
Prioritising areas of interest and investing in the tools to interrogate the right information and get decisions out, at speed, to the right people, is the solution.
The opportunity is clear. Get big data right and organisations can make more informed decisions, understand operations, markets and customer behaviour better and therefore, ultimately, improve the top and bottom line.
the real reason you should be interested in big data is that it can genuinely deliver competitive advantage.