Is there really a difference between BI, AI and analytics? And if so, how do these three technologies work together?
I am often asked to determine the difference between BI (smart business), AI (artificial intelligence) and analysis. For many organizations, there seems to be so much overlap that it is difficult to tell where one technology ends and another begins – or even whether these technologies can be used simultaneously. .
What is business intelligence?
Business intelligence is a broad category of information management, analysis, and reporting that works on both structured and unstructured data. BI can provide insights to organizations about their markets, the “relevance” of their products and services in these markets, and the effectiveness of their internal operations. surname.
The business intelligence toolkit is far-reaching. It may include:
- Standard report
- Analysis report
- Data Mining
- Dashboard
- Performance Management
- Deploying artificial intelligence
Collectively, it is the coordination and implementation of all these technologies that comprise business intelligence activities for an organization.
UNDERSTAND: The best business intelligence tools (TechRepublic)
What is analysis?
Analytics works on both structured and unstructured data to support corporate decision making. It uses standard report-style queries, as well as more sophisticated AI algorithms, to find unique patterns in data and infer insights from them.
Several types of analytics are widely used in organizations – from marketing to operations, finance, customer service, IT, and HR. Analysis can be:
- Diagnose: As in, what fundamental events contributed to the increase in sales last quarter?
- Describe: Are we meeting our company’s KPIs (key performance indicators)?
- Guess: Which components of our assembly line are most likely to fail this year?
- Prescription: What is this online buyer likely to buy next, based on past purchase and browsing history?
UNDERSTAND: Top data analysis tools (Datamation)
What is artificial intelligence?
Artificial intelligence is “intelligence demonstrated by machines, as opposed to natural intelligence displayed by animals consisting of People. ”
In the context of BI, AI can combine human-provided input (from subject matter experts, research, etc.) with machine learning (ML) to identify patterns in data. Then the AI starts making inferences based on this pattern recognition.
AI mainly relies on complex statistical algorithms developed by data scientists to interrogate an array of structured and unstructured data. In this way, AI can generate insights to support decision making. It can also be used to run processes automatically without human intervention.
For example, one use case for AI is in the credit card industry, where a system is trained to look at consumers’ card usage patterns and identify potentially fraudulent behaviors.
UNDERSTAND: Top AI Tools & Software (eWeek)
What is the difference between BI, AI and analytics?
BI, AI, and analytics all provide insights that enable organizations to perform better, predict the future, and meet the needs of their market. However, there are some fundamental differences between these concepts in terms of scope and functionality.
Business intelligence is an overarching framework for analytics and AI. Conversely, analysis can be used in a more independent fashion if desired. For example, a sales team might purchase analytics software so it can assess the market.
UNDERSTAND: Hiring Department: Artificial Intelligence Architect (TechRepublic Premium)
AI automates reasoning processes to eliminate or reduce human work. For example, an industrial robot with built-in AI could perform an operation on a manufacturing assembly line that was previously performed by a human.
Can you use BI, AI and analytics together?
Analytics and AI can be integrated into a larger BI framework, but they don’t have to be.
The advantage of integrating AI and analytics tools into one BI technology stack is that you have the end-to-end operations, decision-making, and data management infrastructure for your business.
If you choose to do this, the first step is to develop a BI framework to accommodate both analytics and AI.
The next step is to populate this framework. For example, where will you use analytics in your organization, where will you automate with AI, and how will you facilitate data sharing throughout your company?
