Data is one of the most important assets in a business, we agree. But what happens when there is so much data that it’s impossible to access it or perform a simple query?

Transforming all this stored information into action remains a challenge for teams, as they often struggle to interpret the data or even access it quickly, due to systems with many technical complexities that force them to rely on IT teams, who are naturally overwhelmed.

As you can see, the outlook is anything but agile or encouraging. Fortunately, Artificial Intelligence has infiltrated many industries to enhance and improve processes, while also facilitating many tasks for teams. And in the field of data analysis, AI has had a particular impact in recent years.

In this article, we’ll discuss how data analysis with AI is booming, the benefits and use cases in business, and how this AI solution streamlines decision-making and the management of key data in companies.

What does it mean to “chat with data”?

When we talk about “chatting with data”, we mean that there are currently platforms that allow users to interact with their information through conversational interfaces powered by artificial intelligence.

And consulting data is literally like having a chat conversation with a coworker: you ask a question in natural language, as you might ask a human, the system analyzes the query, executes the search, and returns the expected result in seconds.

These types of AI solutions eliminate the technical barriers that have existed in offices for years. Consulting information from databases required the support of technical staff, as they had to write queries in SQL, understand the structure of the tables, know how the data is related, and wait for this same technical staff to execute the query.

How many hours would an employee have to wait for a report with the requested information? Many.

Now, with AI data analysis tools, it’s simple: companies’ databases can be connected to these tools, and the tool understands and contextualizes the information, enabling it to provide answers to users’ questions.

A hypothetical question might be: “What were sales in Latin America last quarter?” And the system might respond: “500 units of your product were sold in this region.” It’s as simple as that.

The role of AI Solutions and language models in data analysis

LLMs are key in this new way of interacting with data because this technology, when trained with immense amounts of information, is capable of understanding human language and transforming questions into instructions that a machine can execute.

How does an AI data analysis tool basically work?

1. The user asks a question, for example: “What was the average delivery time for orders in August?”

2. The language model interprets the question and transforms it into an understandable instruction for the database.

3. The database query is executed.

4. The AI interprets and presents the results in clear, useful, and natural language. Example: “The average delivery time in August was 3.2 days.”

Benefits of an AI solution for data analysis for companies

• Faster decision-making

With these AI data analysis tools, teams are more autonomous and can independently access the information they need, without having to rely heavily on technical teams.

• Data democratization

Any employee can explore information without technical or scheduling barriers, as they can run queries on the platform 24/7.

• Reduction in operating costs

Manually reviewing databases is time-consuming and complex; however, with AI solutions, teams can automate report generation, saving time and money.

• Greater information accuracy

Thanks to these platforms, teams have clearer access to the information they need, allowing them to be more precise and clear when creating their strategies and making decisions.

Challenges and considerations when implementing AI data analysis tools

– Artificial Intelligence is very powerful, but it’s not magic either. If the quality of the information provided is low, the results will be of the same quality. It’s important that the information you provide is high-quality and clean so that the AI solution works optimally.

– Consult your team and make sure the platform you implement is secure and meets all data privacy standards to protect your information.

– Train your team on how to create the best chat prompts and achieve the best results.

– We always recommend validating the critical results offered by the AI solution, ensuring that human oversight of the results is essential.