Data. What to do with it?
To paraphrase technologist Harper Reed — if you’re not getting answers from your data, you’re just storing it.
Data’s a treasure trove of insights that businesses should be using to base decisions on fact rather than intuition. Better decisions mean better results.
But data is tough to make sense of. Poor data literacy is the second biggest internal roadblock to success for Chief Data Officers around the world, Gartner report. Top that with the finding that 50% of companies won’t have enough AI and data literacy skills to “achieve business value” by 2020.
So, how do we make analytics accessible? Augmented Analytics — the process of automating analytics with AI — can leave more time for expert data scientists to focus on “specialized problems” and give workers outside of analytics teams easy access to the value data has to offer.
These workers are what Gartner calls citizen data scientists.
Analytics is no longer just for analysts.
Augmented Analytics uses Machine Learning to automate analytical tasks that would otherwise need specialized training or skills.
This takes out the busy work, so employees across a business can access and act on the most relevant insights quickly. It’s catching on too:
• 40% of data science tasks will be automated by 2020 (Gartner).
• Citizen data scientists will overtake data scientists in the amount of advanced analysis produced by the end of 2019 (Gartner)
This doesn’t make data scientists less important, it makes their work more important by taking out time-consuming tasks and driving efficiency.
This means everyone in a business is empowered with tools that boost decision-making. Everyone has direct access to insights and data-driven predictions.
Everyone has the answers Harper Reed was talking about.
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Accessible analytics is one of the five things you’d miss out on without augmented analytics tools.
Learn four more in our free white paper: “5 Benefits You’d Miss Out On Without Augmented Analytics Tools”.
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