Differences Between Augmented Analytics and Business Intelligence

Differences Between Augmented Analytics and Business Intelligence

by Katy Yuan, Sr Marketing Manager

Differences Between Augmented Analytics and Business Intelligence

by Katy Yuan, Sr Marketing Manager

Business Intelligence is overdue for disruption.

COVID has made it clear that companies need to drive digital innovation and prioritize technology adoption. To drive better decisions, finding actionable insights in data is a top initiative for IT and business leaders.

However, traditional Business Intelligence tools are no longer sufficient to analyze oceans of complex data. Static reports and dashboards only answer “what” happened in the past, making AI and automation necessary to understand the billions of data points that every company has collected.

More and more organizations today recognize the importance of analytics. And with this, consumer expectations for seamless analytics experiences also increase. Over the last few decades, analytics capabilities have evolved from mere data reporting and business intelligence to its most advanced form today – Augmented Analytics.

What is Augmented Analytics?

Gartner believes augmented analytics is the next wave of disruption for BI and analytics. They define the term augmented analytics as “the use of machine learning and AI to assist with data preparation, insight generation and insight explanation to augment and automate how people explore and analyze data.”

Augmented analytics encourages the democratization of insights to everyone across organizations. With the combined power of machine learning, artificial intelligence, natural language processing, automation, and data visualization, augmented analytics provides actionable insights to decision makers at every level.

To learn more, read our blog on What is Augmented Analytics?

How is Augmented Analytics different from Business Intelligence?

Business Intelligence tools have been around for decades, evolving from traditional report-centric tools to more user-friendly visualization tools. However, augmented analytics takes analytics to an entirely new level by automating, extending, and personalizing the analytics experience to everyone in the organization.

Let’s discuss the main differences between Augmented Analytics and Business Intelligence.

Business Intelligence

Business Intelligence includes various technologies and processes that parse all the data generated by a business and present metrics and KPIs in reports that inform management decisions.

Augmented Analytics

Augmented Analytics combines BI with the powerful capabilities of machine learning and artificial intelligence to augment and automate insight generation and delivery to every decision maker.

Key capabilities and offerings

Business Intelligence tools only produce fixed reports and dashboards as outputs, while Augmented Analytics platforms help users interact with data dynamically with capabilities like search, natural language narrations, and even audio-visual data stories.

Business Intelligence
  • Fixed reports as output
  • Dashboard creation
  • Data visualization
  • Ad hoc analysis
  • Integration with different data sources
Augmented Analytics
  • All BI capabilities, plus some or all of:
  • Machine learning
  • Artificial intelligence
  • Search and data query
  • Natural language processing
  • Natural language generation
  • Real-time actionable insights
  • Automated personalized insights
  • Data stories
  • Decision intelligence
  • APIs and embedded analytics
  • Multi-device support

Questions answered

One main difference between Business Intelligence and Augmented Analytics is in the quality of discovered insights. Only AA can surface actionable insights that inform decisionmaking, leveraging AI and ML to deliver the most timely and personalized intelligence. BI only shows "what" happened in the past, while AA answers "what" happened, "why" business metrics changed, and "how" to make insight-driven decisions.

Business Intelligence
What happened?

BI analyzes historical data and sometimes real-time data to help users understand what changes happened in their business or operations. BI mainly facilitates descriptive analytics that help understand what happened in the past, compare performance, and identify trends and patterns.


A BI report shows that the annual sales in 2019 were 12M and that they increased by 15%, as compared to 2018.

Augmented Analytics
Why did it happen?

AA goes beyond the “what” to find out “why” business changes happened. This helps users understand the root cause and identify key influencing factors.

How can I take action?

AA facilitates prescriptive analytics by providing actionable insights and recommending a course of action. This helps improve the speed of decisions.

What more am I missing?

AA uses AI and ML to analyze data across all possible scenarios and surface related insights. This helps unearth hidden intelligence that users would not have thought to ask about.


Along with descriptive statistics from BI, AA further finds that 60% of the sales growth can be attributed to a specific coupon and that the same coupon can be used to boost sales in other regions.

Intended users

While Business Intelligence tools have attempted to become more self-service, their complexity means that only analysts with technical training are able to master data query and visualization. This often results in long turnaround times on answering business questions, because a single BI team is burdened with requests from the entire company.

In contrast, Augmented Analytics provides automated insights that are easily consumable and actionable. Business users can directly ask questions and receive instant answers, plus AI-powered personalized insights, in easy-to-understand formats. Decision intelligence is truly democratized across the organization for users of all skill levels, and technical resources are freed to work on complex problems.

Business Intelligence

Traditional BI is predominantly IT-led and most used by data scientists and analysts to query data, extract insights, and create reports that answer the questions submitted by business users.

However, self-service BI helps business users to explore data themselves, to some extent, and create dashboards instead of just reviewing reports.

Augmented Analytics

Augmented Analytics democratizes insights across all users and encourages them to become insight-driven decision makers by providing consumable and personalized insights in an automated way. Business users can explore data and get insights anytime they need, without expert dependency or a steep learning curve.

AA also frees up data scientists and analysts to handle more complex analysis, instead of spending time on routine analysis and reporting.

Approach to analytics

Business Intelligence only delivers "What you ask is what you get" - nothing more and sometimes less. Reports and dashboards often lead to new questions, which spawn more reports, leading to a never-ending relay race where both business users and analysts are dissatisfied with the speed and quality of insights. On the other hand, Augmented Analytics automatically delivers the right intelligence at the point of decisionmaking, ensuring that users have all the necessary and relevant information to make data-driven decisions. Ideally, AI-powered analysis generates insights without user questions, surfacing hidden patterns and trends that are undiscoverable by manual analysis.

Business Intelligence

Business Intelligence predominantly functions on the “What you ask is what you get” approach.

Users need to know what they’re looking for when they browse through predefined dashboards or reports for answers. New questions must be submitted to the BI team who then discovers and delivers the required information.

Augmented Analytics

Augmented Analytics takes an automated approach by delivering insights in a search-less manner. Users receive relevant insights automatically without needing to know what to ask.

AA learns the interests and responsibilities of every user based on their past interactions. Personalized insights are delivered automatically, as they happen, instead of waiting for users to query.

Augmented Analytics vs. Business Intelligence: Which is right for your business?

Gartner predicted that “By 2020, augmented analytics will be a dominant driver of new purchases of analytics and business intelligence.” AA makes insights available to all, regardless of technical skill level. It also drives data literacy and encourages insight-driven decision making.

While traditional Business Intelligence tools are useful for building specific visualizations, their utility has been eclipsed by Augmented Analytics platforms. If you want to empower your teams with decision intelligence to make quick and accurate decisions, utilize every opportunity, and increase productivity and profits, then AA is the right fit for your business.

MachEye’s augmented analytics platform transforms data to intelligence for everyone at an organization with intelligent search, actionable insights, and interactive stories. In addition to understanding “What” happened in the past, MachEye also discovers “Why” business metrics are changing and recommends “How” to act based on insights.

Get started with insight-driven decisions with MachEye’s augmented analytics now! Start your free trial today.