Augmented Analytics: The Future of Data and Analytics

Becoming data-driven is a key priority for many brands. With the rising need and importance for data, next-generation technologies and data processing tools are more readily available to organizations of all sizes and across industries. To be able to maintain competitive positioning in their industry, brands need to adopt an advanced data processing tool such as augmented analytics.

Augmented analytics allows the evaluation of data by employing the use of Artificial Intelligence (AI) and machine learning to augment human efforts. The process is more effective than traditional analysis tools because it automates data insights and provides clearer information.

According to Forbes, 89% of industry leaders believe that this sort of data will transform business operations in the same way the Internet did. They predict that enterprises that don’t implement a business intelligence (BI) strategy to gather, evaluate, and apply that information in a meaningful way will be left behind the competition. Allied Analytics predicts that the global augmented analytics market size will reach $29 million by 2025 due to the growing adoption of next-generation technologies such as augmented analytics.

Augmented analytics is currently implemented in the banking, financial services, and insurance industries. The global augmented analytics market is encouraging business awareness of the importance of consuming evolving streams of data from numerous sources, the growing need to increase efficiency and democratize the analytics, and the need to make the work stress-free for data and business managers.


Converting Big Data to Smart Data

Augmented analytics is able to obtain the true essence of insights from regular data. As such, it can improve data insights by recasting regular data into smart data. There are a number of businesses are already focused on evolving smart data analytics solutions to obtain valuable insights from their big data sets. Smart data can help businesses reduce the threat of losing data and improve a series of activities such as product development, operations, consumer experience, predictive maintenance, and innovation.


Benefits for Data Scientists

The greatest benefit augmented analytics will provide to data scientists and technical analysts is that they will no longer have to run routine and basic reports. Augmented analytics will allow data specialists to move forward and use advanced AI and machine learning to solve more complex queries and data science projects.


Benefits for Marketers

Entrepreneurs, marketing executives, and others who fall under the marketing umbrella often depend on analytics professionals for in-depth research, planning, and reporting. This dependency can be expensive and inefficient especially if the analytics team is a third-party instead of being housed within the organization. Augmented analytics will change the way those marketing based individuals perform their daily work as the efficient and layman-friendly augmented analytics tools put the control back into the hands of the marketing professionals.


Influence of Machine Learning

Most people think of robots or virtual assistants like Alexa when they hear the term artificial intelligence (AI) but the field encompasses quite a bit more. The AI application that provides systems the ability to learn and improve from experiences without any programming is Machine Learning (ML).

ML will make more sophisticated analytics available to more people than in previous years. The development in technology allows a user with no training to take a dashboard that someone else built, make choices from drop-down menus to filter the data, double click on a chart to drill down into it, and other basic actions. This move away from an IT-centric model to one in which end users are capable of working with data on their own establishes a different field of play.

Thanks to the natural language recognition and other new AI and ML related technologies, a casual user will be able to generate a visualization based on what he says or types. Without having to understand how to find data and assemble it in a tool, a user can simply type or speak something like, “Show the sales in the mid-western region and compare the first and third quarter as a line graph.” The desired information will be digitally compiled and presented as requested.

That being said, there will remain a large segment of the user population that is unable to extract and prepare data on their own. Someone with a high level of expertise still needs to build those dashboards – assemble the components, the data visualizations, build in specific key performance indicators, and so on. That portion of the analytics will remain the domain of skilled IT experts and data analysts.


Benefits for Users

In today’s modern analytics, we are seeing an amazing amount of low-cost computing power that has the technological ability to self-discover data insights. In addition, the ability of these machines to perform a greater number of calculations at a faster rate than a person can be combined with the infinite amount of computing power available in the cloud is helping us be more productive than ever before. ML allows us to analyze vast amounts of data and find connections between that data at a rate simply not possible for humans.

Until now, this type of inductive analysis was available only to highly educated data professionals via large expensive systems. The increase in availability of this technology means that casual business users soon will have access to this level of data and analytic power. And because the machines can look at vast amounts of data and intelligently derive insights from that data, users will no longer be required to ask a predefined question of the system. The system can discover business-critical relationships in the data and automatically build visualizations, dashboards, or whatever else is requested.



Whether you are a marketing professional or a data scientist, there are a number of benefits to be gained with a switch to augmented analytics. The main benefit of augmented analytics is the availability and access to refined analytical procedures, algorithms, and methods for the average professional user, without training or knowledge of data science or analysis. The more quickly your brand adapts to this technology, the more quickly you will be able to find and leverage growth opportunities.

While we all do a gut check every now and then, it is usually in conjunction with other information we are using to make a decision. A study by the McKinsey Global Institute reports that organizations which utilize data-driven decision making are 19 times as likely to see profitable results, 23 times more likely to acquire new customers, and 6 times as likely to retain their customers.

You can’t track everything but your team can determine which pieces of data are most important to your organization and which data will help you measure progress towards your business goals. Data takes the stress out of decision making and keeps your organization moving forward. Augmented analytics will help you take that work even further as you work to identify trends and inconsistencies to best understand how your marketing efforts are performing, which channels are most effective, and where your efforts require change.

The experts at Strategy Driven Marketing are all about data and analytics. We’d love to deep dive into your business to understand your organizational goals. We can help you determine analytical measures that will let you recognize progress towards those goals and identify challenges along the way. Contact us today to set up a consultation. Let’s get started!

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