Data is arguably one of the most critical elements of an organisation – how can we drive a business forward by effectively understanding our customers and our clients without data insights, analysis and management?
It may sound like a lot to get your head around if you’re in a business that isn’t as close to their data as they would like to be, what’s the solution? – Business Intelligence.
Business intelligence is a technology-driven tool that transforms data into actionable results - aiding all elements of the business, whether strategic, operational, or financial (or usually all three). There are numerous business intelligence applications and vendors on the market today which, used combined, or individually have the potential to revolutionise the way organisations manage and use their data.
Companies understand how integral data is, hence the increase in business intelligence adoption and the increase in business intelligence roles. Whilst we once had the holistic ‘Data Manager’ role, we are now seeing Business Intelligence Managers / Directors and Analytics Directors, through to Developers, Analysts and even vendor specialist roles. Although we see an even spread of business intelligence and analytics roles, the increase in senior level roles is soaring since around Q3 2018. Perhaps this is due to the heavy adoption of BI in companies; organisations are re-structuring to accommodate business intelligence business units.
As the demand for business intelligence has grown and its function expands within organisations, so too has the various denotations of the term. As a recruitment consultant who specialises in the business intelligence space, and studied analytics at university, I find there’s ambiguity on how we define business intelligence – what some call analytics, others call big data, while others simply use the all-encompassing term of ‘business intelligence’.
I am keen to find out from the business intelligence professionals in my network; do we have one definition for business intelligence and what it symbolises? Or does it depend on the organisation, sector, or purpose of what we are trying to do with our data?
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