Artificial Intelligence and Business Intelligence are both very powerful tools when it comes to helping businesses create effective and informed strategies whether it is about development, marketing, sales, or operations.
AI and BI are two distinct mechanisms but they can complement each other very well if implemented correctly and in great balance. While AI refers to computer intelligence, BI is about making informed decisions based on enormous amounts of data through analyzing and visualizing.
An article by Toptal put it very succinctly: “By embracing the confluence of AI and BI, businesses can synthesize vast quantities of data into coherent plans of action.”
How can these two operate hand in hand to create something that exploits both of their advantages to the maximum? Let’s see the different opportunities they can provide.
Natural Language Processing for Analytics
First, it’s best to talk about what Natural Language Processing is in brief. It’s computational linguistics that merges Machine Learning, artificial intelligence, and linguistics together. For most of the time, NLP is used to turn natural language into machine language. To create queries in a very natural, human-like manner that machines can then understand and convert into results.
One way NLP and AI can be used in business intelligence is by having natural queries and asking these in a normal, conversational style, and getting delivered results on any data from a vast amount of information.
Andrés Felipe Londoño Jiménez, Senior Business Intelligence Specialist at Zebra Technologies said in our conversation on AI and BI: “AI can be used to enhance SQL databases by providing predictive analytics, automated insights, and natural language queries. For instance, SQL Server 2019 integrates advanced analytics and AI directly into the SQL Server database, allowing users to use AI functions in their SQL queries”.
So, imagine you ask for something in your huge data database, like “Give me those users’ information who logged in the last 24 hours and made a payment in the business” and all the users who are relevant will appear for you instantly. This is such a huge innovation that makes analytics, filtering, and targeting so much easier than ever before. No more complex queries or not knowing how to track down data. I think it’s truly fascinating.
AI-Driven Data Visualization for Better Decision-Making
We all know that if we want to comprehend large amounts of data, the best way to do so is by visualizing it.
This connects to our previous point, as AI can help you visualize any type of data using natural language queries, natural language generation, and augmented analytics. What is more, it can give you suggestions on what type of visualizations you should use depending on the data type.
It can also create narratives and insights from your visuals and can answer questions about the outcomes in natural language.
Charts, drafts, and dashboards are created by AI just for you to investigate real-time trends and patterns, so you can make instant decisions if needed for better results.
AI Automation and Workflow Optimization
Andrés said something interesting about automation in connection with AI and BI as well: “AI can enhance ETL by automating the process and improving data quality. For instance, AI can be used to automatically identify and correct errors in the data during the transformation stage.”
There are many other things AI is capable of when it comes to automation:
- Data collection
- Data processing
- Analysis and interpretations of data
Automation in BI means that there is less work that needs to be done by people, so there is more time to focus on more complex tasks. It’s always a great advantage that one can save time and energy, while there is AI taking care of the mass data (which is otherwise humanly impossible to comprehend) and automation for you.
Strategic Planning with AI and BI
So, we’ve established that BI can be very beneficial for strategic decision-making, and AI can facilitate that even further.
So the combination of these two allows you to take advantage of, for example:
- Real-time analytics and insights
- Improved predictive abilities
- Decision support that is highly personalized
- Efficiency in your operations
- Strategic agility that allows you to react to sudden changes and shifts, and make the most of opportunities.
So think of BI as something that handles and takes into consideration the most amount of data for the most precise decisions, and imagine AI as someone capable of interpreting that data into better understandable and actionable insights.
Conclusion
In conclusion, combining AI and BI is a transformative approach to business operations, offering real-time analytics, predictive capabilities, and enhanced decision-making processes.
Data visualization, natural language processing, and automation help streamline companies’ operations. We live in a digital world where data is the single most important factor for a business, so integrating AI with BI emerges as a critical strategy to be agile in the market environment.
