The Yellowfin roadmap: Augmented analytics

The Yellowfin roadmap: Augmented analytics

There’s a lot of talk today about Artificial Intelligence (AI).

The term has become a catch-all for smart technology but, when it comes to analytics processing, it’s really about automating as much of the process as possible to make it more efficient. This extends beyond just the human-to-machine interface to include machine-to-machine interfaces. It also encompasses technology that enables users to improve how they analyze their data in combination with some computer-led prompts and processes.

One element of AI that is being promoted heavily by Gartner and other industry heavyweights is augmented analytics. Essentially, augmented analytics is AI that enables automation of the analytical process. This can be used at the data preparation layer, helping users identify which data is important for example. It can also be leveraged at the analytical layer, using algorithms to analyze, identify what’s driving issues and helping users to solve problems. At the delivery capability level, augmented analytics can help identify how to get an insight quickly into the hands of the people who need it the most.


Yellowfin 7.4 is the first step towards augmented analytics


We recently launched Yellowfin 7.4, that includes a number of features that leverage augmented analytics. In this first instance we’ve focused on two use cases:

  • The first use case is to enable business users to analyze data quicker and more effectively.
  • The second is to help users identify things in their data that don’t quite make sense and access insights that help them understand the drivers behind that data.

These changes mean that some analysis will be able to be automated so our customers can focus on what’s important – getting to the insights. Our algorithms have the capability to find and match attributes, and then identify the underlying things that really explain the trend or change.

By showing business users a range of visualisations with a narrative that explains why things are different, they can curate the information and deliver it back to the rest of the user base. So rather than just reacting to data, business users will be able to actually act on it.


This is a game changer for business users


In most organizations, business users don’t have the data they need to run their business at their fingertips. There’s often another individual in the process – the data analyst. So if there’s a skill shortage or you don’t have data analysts in your business, the business user’s request goes into a queue and they wait for an answer.

If we can shorten the time to insight by taking the analyst out of the equation, we can also help analysts focus on critical analysis rather than just answering simple questions. By helping the business user solve these problems, we’re enabling them to do the analysis they need to intuitively and quickly. They can then focus on improving their business.


Our approach is focused on solving for outcomes


This is not rocket science. Business users are currently looking at dashboards and wondering why something happened. Most of our competitors are still only using augmented analytics to create visualisations from a set of data, showing what it finds ‘interesting’. We’re turning that approach on its head, by asking the user to tell the algorithms what they’re trying to solve for.

For example, if we gave the algorithms retail sales data, it might come back and tell us that we sell more blue socks in winter. Now that’s interesting but it’s potentially irrelevant to improving my business. Instead, a user might ask what drives the sale of blue socks. By placing the user in control of the outcome it shifts the perspective and allows them to tell the machine what they know and direct the algorithms.

Our approach may return nothing back – the machine may say there is nothing that predicts why blue socks sell more in winter. That’s fine too, because at least the user knows the answer immediately, and they can move on and focus on something else.

Over the next 18 to 24 months we will be rolling out more features that leverage augmented analytics based on a variety of different use cases. This will transform the experience business users have with their data. There are significant changes on the horizon for the Yellowfin platform that will help us create these features. It’s going to be an exciting journey.