Before digging into examples and best practices of augmented analytics, it’s important to first have an understanding of the term itself. Augmented analytics is a relatively new concept. As one of the pioneers of the rise of augmented analytics, research firm Gartner might have the best definition for the term:
“Augmented analytics is the use of enabling technologies such as machine learning and AI to assist with data preparation, insight generation, and insight explanation to augment how people explore and analyze data in analytics and BI platforms. It also augments the expert and citizen data scientists by automating many aspects of data science, machine learning, and AI model development, management, and deployment.”
The important thing here it to understand how the word “augmented” is being used in the term. With augmented analytics, machine learning and AI are changing the way people actually interact with data analysis platforms. Instead of having to do every process on their own, these technologies can pick up a lot of the heavy lifting. There are a few reasons why augmented analytics is changing how enterprises use data.
Augmented Analytics Best Practices
First, let’s look at some augmented analytics best practices. These can give you a better idea of how you can generally think about applying augmented analytics within your organization.
- Use to Automate Tasks – Anyone who has spent time with data analytics knows there are plenty of small tasks involved that soak uptime. There are a few ways augmented analytics can do this, such as preparing and cleaning data, suggesting follow-up insights, automatically creating visualizations, and other elements. This can drastically reduce the amount of time spent by employees preparing reports while improving outcomes.
- Establish a Data Culture – You know data can be valuable to your business. But how are you going to maximize your return on data assets? One of the best ways to do this is by democratizing data and establishing a data culture within your organization. This is where analytics is used as the go-to source for decision-making across the board. Adopting augmented analytics can help accomplish this because it makes data more accessible for a greater number of employees. In fact, establishing a data culture should be considered one of the top benefits and best practices for bringing augmented analytics into your enterprise.
- Build on Your Successes – You don’t have to adopt augmented analytics and immediately start swinging for the fences. In fact, it’s typically better practice to start with small victories and build on them. Not only does this allow you to gain a better understanding of the tools, but it also lets the machine learning- and AI-powered analysis platforms recalibrate to better align with your underlying objectives.
Augmented Analytics Use Cases
Now that you know a few of the augmented analytics best practices, it’s time to dig a bit deeper and look at a couple of use cases. Here are two ways augmented analytics can alter organization operations on a fundamental level.
- Increase Speed of Obtaining Insights – With the old way of doing data analysis, it could take days or weeks to get the results of a query—by which point, the answer could be obsolete. Thanks to augmented analytics, actionable insights can be obtained in as little as a few minutes. Natural language processing via machine learning- and AI-powered platforms has brought a new kind of augmented analytics feature to the world: search-driven analytics. This is where users can get answers by simply typing them into a feature analogous to a search bar. Not only does this further democratize data, it drastically cuts down on the time between questions and answers.
- Find Anomalies Hidden to Humans – Augmented analytics can take you to places you never would have ventured on your own. There are a couple of ways this works. First, augmented analytics can spot anomalies in data that would normally be missed by humans. This can help prevent critical errors that otherwise could dearly cost corporations. Furthermore, augmented analytics can suggest further intelligent insights based on your search patterns. Through this added layer, you can arrive at solutions that would have been inconceivable on your own.
Augmented analytics are changing the way enterprises utilize their data. Understanding this rising technology and how it can fit into your business will give you a leg up on other firms.
