Working in the Business Intelligence (BI) space means that we deal with data and information on a daily basis. Our role is to ensure we make sense of all the data and information coming into businesses – to the benefit of our clients’ organisations. What astounds me is that even today there are still some organisations that view data and information as interchangeable. While not accurate – the problem this presents is that it can actually have a detrimental impact on the data and BI strategy of any business.
So, what then is the difference between these terms? And, why should businesses even worry about defining data strategy/model that defines these accurately?
Data is the foundation or ‘root’
Data refers to raw facts and figures that are unorganised and almost untouched that have the potential to become part of the information. Data is unstructured and hasn’t been through the process of being analysed (as yet) to make sense of it or to give it a ‘bigger picture’ value. By way of example, if you wanted to find out what kind of people run tech start-ups, you would first need to collect data. To get this data, you must ask specific questions; are tech start-up founders graduates or experienced entrepreneurs? Do they usually hold post graduate qualifications or are high school graduates? Feedback to these questions would then be the factual information and subsequent data.
Data and the ability to collect it is nothing new, however, the way it can now be analysed (and used) is leading us into an era that makes data truly valuable. In fact, ninety percent of the data in the world today has been created in the last two years alone, and we are currently generating roughly 2.5 quintillion bytes a day – that is a lot of data.
Information provides us with the picture
When data (which, remember is raw) is given context – through analysis and then put into a structure, it becomes information. Referring to our tech start-up example above, the understanding of whether founders of tech start-ups are experienced or not would be useful information. For example, if 100 tech start-up founders participated in the research, and through data gathering you managed to categorise them as ‘graduates’, ‘experienced’ and ‘not experienced’ in a tracking document – then, by analysing the data, you can then create a picture or tell the story. For example, which group of people excelled quicker when it comes to building a business – and did their qualification, or lack thereof, aid or hinder them in establishing their business?
Data and Information Guide to Intelligence
As a passionate advocate for data, I am honoured to be chairing a two-day conference, which takes place on the 28th & 29th November 2017 in Melbourne, Australia. The Data and Information Guide to Intelligence Conference is specifically aimed at examining the difference between data and information (in their separate entities), addressing how businesses can gain intelligence from each – which for me personally, is key to any BI and data related strategy.
So, for those in the surrounding area, if you want to come and debate how businesses are continuing to deal with the amount of data and information flowing into organisations from all difference sources, please join us. This this is certainly going to be an interesting event and hope to see some of you there.
