- What is augmented analytics
- Which are the three ingredients of augmented analytics tools
- How augmented analytics tools can help you free up at least 40% of your time
- And, how to use augmented analytics tools to empower your teams
Three concepts form the backbone of augmented analytics tools:
- Machine learning
- Natural Language Processing (NLP) and
- insight automation
Do you know how much time augmented analytics tools can save your company? Gartner predicts that over 40% of data science tasks will be automated by 2020, resulting in increased productivity and broader usage of data and analytics by the so-called citizen data scientists.
More specifically, Gartner says that citizen data scientists can “bridge the gap between mainstream self-service analytics by business users and the advanced analytics techniques of data scientists”. These scientists are now able to perform sophisticated analysis that would have required more expertise; this enables them to deliver advanced analytics even if they don’t have specialized skill sets that data scientists do.
To be clear, this automation won’t just benefit data scientists and data teams. Gartner, once again defines a citizen data scientist as a person who creates complex descriptive and predictive models, but whose primary job function is outside the field of statistics and analytics. If you’re, a sales manager who’s tasked with putting together reports for board meetings, you can also skyrocket your productivity with augmented analytics tools.
Interestingly, Gartner also predicts that citizen data scientists will surpass data scientists in the amount of advanced analysis produced by 2019. According to Gartner, businesses today are increasingly being powered and impacted by analyses produced by citizen data scientists. This doesn’t just create a more data-driven environment, it also allows data scientists to shift their focus onto the more complex analysis.
But how, exactly, can you use augmented analytics tools to empower your teams? Here are a few use cases of augmented analytics that can help to boost your team’s productivity:
- Automated data cleaning and compilation
- Identifying patterns and trends in key metrics
- Tracking actions and strategies to identify effective approaches.
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