What is Big Data?
Let’s start off with what Big Data is not…
It is not the physical data centre that hosts your colossal amounts of data –
The servers on/off site that store your company data
It is not the sheer volume of data that is simply the referred to as Big Data –
Your company’s emails stored for the last 15 years.
It is the data analysis scenarios that process hundreds of terabytes/petabytes of data to answer a given question
The best way I think to explain Big Data: It is about putting all possible relevant data together and finding relationships and clusters that we didn’t know were there in the first place.
To provide an idea of how much information terabytes and petabytes represent, see the examples below:
Courtesy of computerhope.com
Another term often associated with Big Data is Data Scientists. These are the experts that carry out the scenario processing using a variety of different analytical methods. No longer can we use the traditional rational database queries of Business Objects and Microsoft query to manage the processing of scenario analysis. There are just too many dimensions required to be considered in the processing methods.
What is scenario analysis?
Key to Big Data Analytics is the processing of scenario based analyse; the process of analysing future events by considering alternative possible outcomes (sometimes called “alternative worlds”)
Imagine that you’re facing a really significant decision, which could fundamentally affect your personal life, or could determine the future of your business. Maybe you’re thinking about “stretching your finances” to buy a bigger house. Or maybe you’re thinking of launching a new product which you know could “cannibalize” existing sales.
Perhaps you’ve done the numbers, and these seem OK. But deep down, you dread what could go wrong. After all, no one has a fool-proof vision of the future, and while you may have strong instincts as to how things may develop. Any single projection of the future is clearly vulnerable to disruption by a range of different factors.
Scenario Analysis helps you bring these fears into the open and gives you a rational and professional framework for exploring them.
Using it, you can make decisions in the context of the different futures that may come to pass. The act of creating scenarios forces you to challenge your assumptions about the future. By shaping your plans and decisions based on the most likely scenarios, you can ensure that your decisions are sound even if circumstances change.
Examples of scenario Analysis
The analysis is designed to allow improved decision-making by allowing consideration of various outcomes and their implications. Scenario analysis can also be used to illustrate “wild cards.”
Analysis of the possibility of the earth being struck by a large celestial object (a meteor), whilst the probability is low, the damage inflicted is so high that the event is much more important/threatening than the low probability (in any one year) alone would suggest.
Every time you perform an internet search, post a tweet or blog, send an email, use your mobile or shop online to name a few, you leave behind a trail of data – a digital footprint of your lifestyle, financial activities, social interactions, health habits and much more.
Take loyalty cards, they know what you buy in which store, at what time of day and how often. Imagine if all this data along with your data from many other sources is collated and analysed.
The power of the data and what will be known about you is immense. Ways in which this “Big Data” can create value accordingly to McKinsey & Co are:
• Make information transparent and usable as a far higher frequency
• Let organisations collect richer and more accurate performance information
• Allow narrower customer segmentation
• Dramatically improve decision-making
• Improve new products and services
Concerned about your personal security, I will discuss security in a later section.
The 2012 election was a watershed event for leveraging technology in the political arena. Both the Obama and Romney campaigns relied heavily on technology. Obama’s team created an app “Obama for America” which connects all the people who are in favour of him, allowing neighbourhood campaigns to be organised. The supporters could create a profile, join groups, arrange events and raise money. Over 2M people signed up.
Experts believe that the tactics and analytics used to gain support and influence people and get them to vote, can be applied by enterprises to influence customers and drive sales. Apps for use while shopping are already with us with more complex analytic versions in development and your fridge telling the store your shopping order!
Amazon is using it not just for feedback or purposes but to satisfy its customer when they come back with problems, i.e. Amazon is using all this data in its customer service department to solve customer problems. Say an angry customer calls and instead of telling you his problem, you tell it…that would be cool right! Can you imagine the positive effect it will have on your brand and of course customers will no more be angry (we can only hope).
More on Big Data and how it affects your business in future posts.
What examples of Big Data in use do you have?