Business Intelligence, Artificial Intelligence and Advanced Analytics – What’s the Difference?

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Advanced analytics is often confused with business intelligence and artificial intelligence. To have an accurate understanding of advanced analytics, it is essential to identify how it is different from its counterparts.

Advanced Analytics vs. Business Intelligence (BI)

Advanced analytics can often be confused with business intelligence. However, the former is a more in-depth study of market forces, using much more complex techniques.

Business intelligence and advanced analytics are both tools used to equip businesses to make more informed decisions. Each tool is different, however, and provides different outcomes and benefits. Business intelligence is used to make better business decisions through searching, gathering, and analyzing accumulated data.

Business intelligence differs from advanced analytics in several key aspects:

Business intelligence focuses on using historical data to identify ways of improving current performance while advanced analytics provides businesses with predictions of future events and the best steps to take to make the most of the changing future.
Business intelligence is a simpler analysis to address simple issues in the market environment while advanced analytics employs a combination of sophisticated tools to provide a more layered, complex understanding of the competitive environment.
Business intelligence is a reactive approach towards understanding the root cause of an event while advanced analytics is a proactive approach to identifying various what-if scenarios in the future and helping prepare for it.

Simply put, business intelligence is a basic approach to understanding the past to improve the current situation. Advanced analytics focuses on a complex study of possible future events in the market and on all the possible means of dealing with those future events in the most productive manner.

Advanced Analytics vs. Artificial Intelligence (AI)

Advanced analytics and artificial intelligence are also similar tools, but used for different tasks. AI is the subset of advanced analytics and involves automating steps that normally humans would take to complete an exhaustive analysis.

Advanced analytics is a broad term used to cover a variety of technologies with AI being one of its components. Advanced analytics is made up of these three technologies: Predictive analytics, prescriptive analytics, and artificial intelligence.

Predictive analytics uses statistical modeling to predict future scenarios. Prescriptive analytics employ optimization and rule-based expert systems to solve supply chain problems, essentially providing recommended actions. And finally, AI is the most advanced form of analytic technologies such as machine learning and deep learning, which are AI-based and interactive with business users.

Artificial intelligence is particularly distinct from the other two more traditional components of advanced analytics (namely predictive and prescriptive analytics) in that it can learn and evolve with time and it is capable of processing natural language.

Artificial intelligence (AI) can now understand human language in a manner that’s remarkably similar to human understanding. This is known as artificial neural networks, which are an area of machine learning modeled after the biological neurons and synapses within our own brains. Google researchers have figured out patterns for speech recognition; they were able to not only recognize what we said but also translate it into text by understanding grammar rules like “I am running every day this week.” They achieved these breakthrough results without having been explicitly taught those particular grammatical conventions. The more advanced AI becomes at processing natural languages–and interpreting them when necessary—the closer computers will come to true comprehension from voice commands or typed queries.

Simply put, advanced analytics involves the use of a much broader range of technologies to help a business develop a deep understanding of the complex market factors while AI is a more specialized subset of technologies under advanced analytics.

Using Business Intelligence, Artificial Intelligence, and Advanced Analytics Together

While we can now see how each of the three terms are distinct from each other, we can also recognize that they are related to one another and capable of complementing each other extremely well in context to helping a business improve its overall performance.

All three tools help businesses make informed and effective decisions. Used together, they can help businesses analyze past performance, establish key correlations, extrapolate future trends, and recommend the best courses of action for the future to improve business performance.

To make sure that your company is using these technologies to their full potential, it’s important to remember that each one of them has its own strengths and weaknesses. For example, business Intelligence provides deep insights into the past while AI helps with predictions about the future. Artificial Intelligence can process large amounts of data quickly which is perfect for big businesses but not so much for a small one. And, advanced Analytics processes real-time data streams extremely well.

Effective utilization of business intelligence and advanced analytics by a business can actually help a business plug the weaknesses that exist in its current configuration all the while building greater capabilities and being better prepared to capitalize on future market opportunities.

By understanding how each tool works best and building an effective strategy to use them together, your company can be in a better position to take advantage of all the benefits that each technology has to offer.