It's no secret that tracking your analytics is vital to transforming your company into a market leader. In today's technology-centered world, analytics helps us pinpoint where our traffic is coming from to put more effort into campaigns that have proved successful. Recently, the concept of augmented analytics has come to the forefront, in what Gartner calls "the future of data analytics."
Gartner describes augmented analytics as "an approach that automates insights using machine learning and natural-language generation, marks the next wave of disruption in the data and analytics market." But what exactly does that mean, and what problems can it solve?
What is the Challenge?
Today, we can all agree that data analytics is essential to improving your business. You're able to track your traffic and see what's working and what's not. You can determine different ways to reach higher conversion rates, better visitor numbers, and increased revenue. However, a lot of the data that you see may not be as straightforward as you like.
On the surface, it may be hard to discern if the trends you are seeing are specific to your business or if they are happening all over the industry. Without digging deeper, it's hard to know what you can do to give yourself the best chance of success. In short, the data by itself doesn't do much to help you. Instead, you need to know what to do with those numbers.
How Can We Fix It?
Data alone can't help, knowing what to do with it is the key. One route to get your numbers into action is by hiring a data scientist or analyst. This approach is a good one; however, there are caveats. Hiring one will come with a high price tag, and as is the case with all humans, they can only do so much work and are sub are subject to error. Data scientists are certainly not going anywhere, and they are a vital part of the business community as a whole. However, it may be hard to overlook the shortcomings.
Augmented analytics is helping to solve these issues and make it easier for the average businessperson to get more out of their data.
What Can Augmented Analytics Do?
Essentially, augmented analytics uses AI algorithms and machine learning to do the jobs of data scientists, but much faster and cleaner. For example, while a data scientist may only be physically able to analyze 10% or 15% of your data, augmented analytics can analyze all of your data in less time. This gives you faster insight into your numbers so that you can act on them most efficiently. Additionally, much of data scientist time on the job is spent doing mundane tasks like labeling data. With augmented analytics, however, these tasks can be done in a snap, so everything is always in its place without human intervention.
Using augmented analytics is also much more cost-effective for business owners. Since this software can work much faster than a human, you have the benefit of using dollars for more meaningful initiatives than for paying high hourly rates. Finally, augmented analytics can operate with virtually no supervision, making it easily accessible to any business owner, regardless of how tech-savvy you are.
The Future of Augmented Analytics
We should be clear that augmented analytics is still very much a developing field. There is always a place for data scientists and analysts in today's world, and we're not quite ready to fully make the shift to augmented analytics. However, as with most emerging technologies, this concept is growing incredibly quickly, and we will see much development in the coming years.
Today, most of the augmented analytics companies that we see are still in the development process. While using this technology can be a great addition to your business, it may not be mature enough to stand on its own yet. In the coming years, we are likely to see augmented analytics become stronger in the areas of signal detection and insight generation.
Typically, the augmented analytics that we see today is used for mundane tasks such as data collection and labeling. In the future, augmented analytics will be able to find the trends in your data, connect these trends with your specific scenarios, and make informed insights on what to change.
In conclusion, augmented analytics is already a helpful tool for businesses today, but it is not a replacement for the data analysis you may be doing. As the technology continues to grow, it will help business people of all skill levels to make the most efficient use of their data. In the next five to ten years, augmented analytics may prove to be an irreplaceable tool for business owners. If it achieves its promises, it can become a cost-effective, quick, easy, and reliable way to track your analytics and discover how to improve them.
