– A business leader’s quick reference to machine learning in business intelligence tools
As a business leader, you don’t have time to sort through pages of technical explanations. So, let’s get right to the point.
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According to the 2017 Gartner Report: Magic Quadrant for Business Intelligence and Analytics Platforms, “By 2020, natural-language generation and artificial intelligence will be a standard feature of 90% of modern BI platforms.”
Yellowfin BI has emerged as an early leader, now using machine learning (a subset of artificial intelligence) and natural language generation in their dashboards to speed time to insight. We call it Assisted Insights. You can expect business users to be able to find interesting points of insight within their dashboard and immediately get answers to their “why” questions with the click of a button. This means you no longer wait for a data analyst to provide answers to basic questions asked by the business.
What is it?
Business intelligence has evolved from reports that show users what happened to interactive dashboards where users can drill-down to discover why things happen. The human discovery process is now being augmented with machine learning.
Yellowfin uses machine learning to mimic the work normally done by a business user or data analyst. Behind the scenes, Yellowfin scours the data, decides which algorithms to run on the data, picks the best, runs the algorithms and returns the results to the business user. The more automated insight that is used on the data, the smarter it gets. Unlike humans, it never forgets. Imagine the potential of human insight augmented by machine intelligence.
What does it mean for the business?
1. It means you don’t have to wait for answers.
When you find interesting points within your dashboard, all you have to do is click on a button to explain or compare these points. For example, you may see that sales were higher or lower than usual in a certain month. Within seconds after you request Assisted Insights right within your dashboard, you will get back a set of visualizations and narratives about what caused the increase or decrease in that month.
2. It means having a data-analyst as your personal assistant.
In the old world, without machine learning, you would have taken a screenshot of the dashboard, pasted it into an email, and sent the email to a data analyst, asking about what happened in that month. Depending on the workload of the analyst, it would have taken hours or days to respond. Chances are the response wouldn’t really answer the question you were asking, so you’d have to go back through the same process again. Assisted Insights replaces that entire process and eliminates the need to go through an analyst to get answers. Assisted Insights becomes your personal data assistant.
3. It means more data-driven decisions.
When you get answers instantly, you can act quickly. By cutting days out of time to insight, you will be able to make more data-driven decisions. When you make more data-driven decisions, you will be able to work in cycles of continuous improvement and bring more value to the business.