Augmented analytics lets smart analysts jump to conclusions

Jumping to conclusions has always been considered a bad way to do business (and most things in life). It implies making a rash, poorly considered decision without the facts and without an understanding of the wider implications associated with that decision. But there’s a new wave of technology that is changing everything. Automation and AI are bringing us ‘augmented analytics’, and certain augmented analytics tools are providing the shortcut to insights that enables analysts and business users to jump straight to the conclusion.

What is augmented analytics?

Augmented analytics is the use of machine learning and forms of AI to automate and enhance the process of getting from data to insights.

Hours, days, weeks and sometimes months are spent in the often manual and labour-intensive process of unearthing insights - golden nuggets of explainable change in the data - that will help businesses optimise.

And this pace of data-to-insight is lagging far behind the pace of today’s data deluge into businesses.

With increased volume, velocity, and variety in business data, analysts simply cannot keep up with analysis. And with so much data to sift through, there is an inherent  human bias going into the choice of which data sets to analyse and how. You can’t filter and drill for hours on end without getting a little rash in your decisions about what to analyse. You end up only looking at the datasets that have produced results before.

Bias and fatigue are huge problems in analytics today.

However, the automation we get with the new era of augmented analytics promises to change all that. It will, in fact, entirely automate the majority of the workflow steps and radically reduce the human hours spent in the analytics process.

The evolution of analytics

Business analytics was once the domain of IT specialists.

The tools were very manual, complex, and extraordinarily expensive. Analytics has shifted from those days of static dashboards built from data silos to the more recent interactive visualizations built through self-service analytics that even have some natural language add-ons.

Today, everything is changing again. You can see the disruption of the market with insights-driven analytics that prompts you to action with tailored notifications of automated data discoveries. This is the new wave of automation. This is augmented analytics.

Insights when you need them with augmented analytics

How long does it take you to find an insight in your business data?

It depends, I know. But what about that query from Marketing about the weird drop in the website traffic? Or the query about the spike in travel expenses that came from Finance?

It might take a day of analysis. But how long was the queue of other requests that you had to get through before you got to that latest query? Often, that query is only answered long after it was needed, and there’s a ton of work involved.

From Traditional BI and Analytics Workflow

To Yellowfin Signals -  Automated Analytics and BI Workflow

There is a multitude of steps to the analytics workflow.

So what if you could shortcut the process? What if you could let the machine do the heavy lifting of discovery so you can jump from data prep to actionable conclusion?

What if you could simply do:

1. Data preparation.
2. Wait for a signal of change to pop up as a notification so you can share and act on it.

That’s the promise of automated (or augmented) analytics. It helps you jump to conclusions. The analysis in the middle is done for you, not skipped. The technology can compute so much more data than a human and in a fraction of the time, that it makes sense to let the technology do the work in such a deluge of data.

Plus, the machine can always be running and therefore alert you to changes as they happen. Delivering notifications of dips, spikes, trend changes, period comparisons, and more. That means you never miss a critical change in your business again.

Benefits of automated analytics:

• Fastest speed to insight
• It always stays on top of critical changes in your business
• Less bias and no fatigue in the discovery process
• Reduce costs spent on time and people

Are analysts out of a job now?

With all this talk of the speed, power, and accuracy of automation, you might think the analyst is dead. But no. The analyst is still desperately needed.

The new analyst role

As automation delivers these data signals at the speed of the machine, the role of the analyst must evolve to one of an insights interpreter. They must surface the most important insights and ensure the correct course of action is taken. To adapt to this new wave, today’s analyst will need a very different blend of skills.

The new analyst needs to be an expert at root cause analysis as well as being business savvy. To sift out the most important insights, analysts will need to know what is important to different users and departments. This requires an understanding of the implications of that business data. How can an analyst know to investigate a significant spike in web traffic from one location if they don’t know the implication of that information to the marketing team? Analysts need to deliver insights that are meaningful to each business unit so they can affect their area of influence.

You need to start preparing for the future of analytics teams in your business today. (You can read our white paper on the future of analytics departments.)

Jump to the conclusion

With automated analytical capabilities, like those of Yellowfin Signals, you can see how you can shortcut a whole swathe of manual processes and jump straight from data to insights in minutes, not days or weeks. You’ll be jumping to conclusions that help your business, fast.