27 September 2018
Augmented analytics: The new face of BI & analytics
A Future with Augmented Analytics For decades, the looming promise of a world where humans are no longer useful has been beckoning us. In this future world; our smarter, more efficient and overall better machine counterparts rule as the cogs that keep our world ticking, whilst humankind is left unemployed and largely undervalued...
But what if the promise of better and more efficient processes didn’t necessarily have to come at the expense of human jobs?
What if there was a new technology that could actually help to increase the value of human expertise rather than diminishing it?
The future of BI and analytics is set to do exactly this. A new technology is emerging and it’s expected to change the face of BI and Analytics as we know it by as early as 2022 – all whilst empowering human intelligence more than ever before.
What is this new technology? Well, it’s called Augmented Analytics and it’s defined as:
“An approach that automates insights using machine learning
and natural-language generation.” (Garner, 2017)
What's there to be excited about?
Some call it Augmented Analytics, others call it Smart Data Discovery, but at its core, it involves the fusing of BI with AI to automate the processes of finding data, preparing it for analysis and generating insights.
The manual process of turning raw data into useful insights is typically a lengthy process involving numerous steps.
First things first, before any analysis can be done, a super-defined research question has to be established. The problem with this is that it becomes a lot like cherry-picking, as with choosing to focus on one single question, certain data is automatically disregarded and therefore some insights are never explored.
Once a clear research question has been defined, businesses then have the task of building an algorithm or model. This is no overnight process and involves a considerable amount of time and manual labour.
After these two steps are finally completed, then comes the most difficult part – translating this disparate data into actionable insights, all whilst minimising the uncontrollable force of human bias.
Augmented Analytics makes life easier
Augmented Analytics makes this easier by automating the process of analysing data and generating insight.
It identifies trends and explains what these practically mean for a business through clear visualisations and neatly packaged trends. One feature of Augmented Analytics that sets it apart from other technologies is its ability to carry out “natural-language” generation, which unpacks complex jargon and provides insights in simple, digestible terms like “56% of leads were generated from PPC ads”.
On top of this, Augmented Analytics eliminates the restrictions that human bias can bring. It isn’t bound to a specific research question and it gives organisations the freedom to uncover the numerous layers of insight that their data has to offer – even providing insight that was never considered in the first place.
All in all, this means that executives are free to focus their attention on the strategy side of things rather than getting tied down by routine computational tasks.
Some estimate that once Augmented Analytics reaches its peak, it will remove the need for data scientists and analysts. However, experts agree that in reality, the most likely outcome is that these roles will simply evolve to become more focused on specialised problems and on embedding models in enterprise applications, working hand-in-hand with Augmented Analytics to carry out their roles more efficiently.
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The beauty of Augmented Analytics
The purpose of Augmented Analytics isn’t to replace the decision-making process, but to support it.
The beauty of Augmented Analytics is that rather than replacing the need for certain technical roles within an organisation, it actually helps to leverage human expertise.
Instead of spending months preparing and analysing data, executives are given the keys to unlock clear trends, visualisations and insights at their convenience. This works to help support business decisions and allows experts to carry out their jobs with greater accuracy.
With Augmented Analytics, human expertise actually becomes more crucial than ever. The abundance of insights offers the temptation of getting caught up in “shiny object syndrome” as each insight potentially offers equally as exciting possibilities to explore. Experts will have to combine their expertise with initiative to sort through these nuggets and pick out only those that coincide with the wider business strategy.
These more extensive insights will also challenge experts to dig deeper to provide even greater value to the business and will give them an instrumental role in ensuring that their organisation is driven by data.
Ultimately, Augmented Analytics will strip out the dull, robotic processes involved in BI and empower employees to focus on being human.
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