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Augmented data discovery is going to make it much easier for business users to find insight from data.
We’re working on some exciting features as part of the Yellowfin product roadmap. So I thought I’d share one of these to provide some insight into how our product is evolving for our partners and customers.
One of the most interesting parts of our roadmap is Augmented Data Discovery. This is a significant improvement from the good ol’ days of manual data discovery. For too long, end users have been left to sift through data searching for outliers and then trying to work out what it all means. This isn’t an efficient use of your time and it doesn’t give you what you want – the specific data points and insights that are important to you.
By using some smart algorithms, Yellowfin will soon prompt you and guide you through your data. At the same time, the platform will learn what’s important to you. Once it knows what you are trying to discover in the data, it can then present that back. By taking a user-focused approach, data and insights become more relevant.
Augmented Data Discovery is a natural step in the evolution of BI
Historically, analytics meant static reports that were held centrally. This evolved over time and became nimbler thanks to the introduction of toolsets that enabled people to do their own discovery. Any business user could sift through data manually to uncover insights.
This is still the predominant way most analytics are used today. You start with an unknown dataset and then find insights within it. The problem with this approach is that the business is essentially starting from scratch each time because they don’t know what they’re looking or where insights might exist.
With augmented data discovery, our algorithms do the heavy lifting of sifting through data and then presenting the user with insights that can really make a difference to their business.
The beauty of this approach is that it looks at analytics from the perspective of the end user. What are they trying to achieve? How can data help them find useful insights rather than presenting them with a range of random things? (of which 80 percent are probably irrelevant)
With this as context, we see three broad use cases for augmented data discovery:
- Speeding up discovery
- Understanding the why
- Automating analysis
1. Speeding up discovery
Manual data discovery can be very time consuming. By automating the discovery process Yellowfin will speed up the process of analysis. For example, we can rapidly generate visuals that will show business users how they can improve the efficiency or profitability of their organization.
A user creating new analysis on an existing dataset, or creating a new dataset, will be able to quickly discover insights in the data. We’ve built some smart ways to identify attributes that they’re interested in and then present those insights back quickly and in a visual way.
2. Understanding the why
If data tells you that sales in January are up 50% compared to December, this is great, but it doesn’t tell you why the change occurred. What’s valuable to the business user is not just knowing the outliers, but understanding what drives them.
Our augmented data discovery engine can rapidly identify the anomalies or outliers in a dataset, then identify the key drivers. It speeds up the process by cutting out the need to go back to the data analyst to run additional analysis.
3. Automating analysis
This use case brings together the two use cases mentioned above and automates them. Overall, this means a significant change from the typical data investigation process, where a user performs analysis on selected datasets. Instead, we’re moving toward an approach where we provide our customers with a digest of analyses that may be of interest to them.
Our customers are excited
Every client I’ve spoken to about augmented data discovery has been excited by it. They see the potential to simplify their entire process of analytics delivery and give their end users a product they can actually use. Their feedback has given us the impetus to bring this to market as quickly as possible.
We expect to have the fully featured version of Augmented Data Discovery ready for our 7.4 release, which will hit the market in October.