It’s rather fitting that on the day that I write this, it is 30 years since Tim Berners-Lee outlined his proposal for the World Wide Web. It seems difficult to comprehend how business was once done without the internet and yet for a very long time, it was the norm. No doubt some of you can still hear the whirring and grinding of dial-up.
Advances like the World Wide Web have done nothing short of change the world. As we look to the future, new developments in AI and machine learning are lowering the barrier for entry for companies seeking to maximise value from their data. Might businesses look back in another 30 years and wonder how they operated without these tools? Despite how the future might look, the opportunity to develop and utilise data effectively is not some futuristic ideal. It is available here and now.
Effectively maximising value from your data requires a great deal of consideration. Conflicting stakeholder interests, data protection and limited integration can all prevent a business from making the most of its data. When approaching a new project, the first set of questions we’ll often ask is:
- Are you collecting the correct data?
- What are the sources and where are they located?
- Who has ownership?
- Are there any data protection implications?
- How is it formatted and structured?
Rubbish In, Rubbish Out
Like a lot of things, the value we get out of something greatly depends on the effort we put in. Effectively utilising your data in the decision-making process requires data not only of a sufficient quality, but also of a sufficient quantity. The better the quality of your data, the greater the depth of insight that can be gained. The more data you have, the more representative those insights become.
Understand your intentions
We’ve spoken previously about the importance of getting to the heart of your business problem. Understanding your objectives is the first step in effectively utilising your data in the decision-making process and it is important to have a realistic understanding and appreciation of what your data can do.
Not all data is created equal. Different data sources and formats often mean that processing is required before actionable insights can be made. The Extract, Transform, Load (ETL) process seeks to do just that, by unifying different data sources in a consistent format. With the data prepped and ready for ingestion, an engineer can build a database and set the data up in such a way as to enable the data scientists to ask the appropriate questions.
Fig. 1: Extract, Transform, Load
What does the future hold?
Effectively utilising data in your business no doubt seems like a daunting task. The World Wide Web was no different. Despite being involved in its creation, Robert Metcalfe wrongly predicted that the internet would collapse (33m35s), yet here we are 30 years since its inception and it now seems impossible to imagine how businesses ever functioned without it. (Metcalfe famously ate his words.)
Organisations need advice on how to align data policy and approach to their decision making. We consult with organisations to help them understand the data they have and how to frame the question effectively. To find out more about what we do and how we do it, click this link.