Mini guide to Business Intelligence (BI): transforming data into strategic decisions

Up to this point, we've discussed the concept and importance of Business Intelligence . But in practice, how does it work? How does a set of scattered and disorganized data transform into something visual, strategic, and useful for decision-making?

BI isn't magic that happens overnight; it's a process. Understanding this process helps to see BI as a cog in the machine that connects to the daily operations, management, and strategy.

It all starts with data. But for it to truly generate value, it needs to go through a series of steps that go far beyond simply "gathering information ." Each of these phases plays a fundamental role in the quality and applicability of the insights that will be generated. Learn more below.

The stages of BI: from data to insight

The Business Intelligence can vary depending on the company's data maturity , but in essence, it usually follows these steps:

1. Data collection : This is the starting point. Data can come from various sources (ERPs, CRMs, spreadsheets, social networks, financial tools, among others). The challenge here is to ensure that these sources are accessible and securely integrated.
   
2. Data processing and organization : raw data is rarely ready for analysis. This step involves cleaning, standardizing, enriching, and structuring the information; all so that the data becomes reliable and usable .
   
3. Storage : The processed data needs to be centralized and stored in a way that facilitates querying and scalability . This can happen in relational databases, data warehouses , or data lakes , depending on the volume and purpose;
   
4. Analysis and visualization : With the data ready and organized, we enter the phase that is most connected to operations. This is where dashboards , graphs, reports, and alerts come in, allowing you to track indicators in real time and understand what is working, and of course, what needs adjustment .
   
5. Decision-making : BI truly comes into play when the insights generated guide practical decisions , such as redirecting resources, adjusting campaigns, prioritizing initiatives, or responding to risks before they escalate into crises.

It's important to know that these steps are not static. In more mature companies, this cycle runs continuously, feeding back into itself and improving over time .

Tools that enable BI

Business Intelligence strategy can withstand mere intention. Technology plays a decisive role in every step we've seen so far.

Therefore, BI tools were created precisely to transform complexity into clarity . They integrate sources, automate processes, organize data, and translate it into accessible visualizations, even for those who are not technically skilled . Among the best-known solutions on the market are:

• Power BI : a Microsoft tool with strong integration with Excel and the Office ecosystem, ideal for companies already operating in this environment;
  
• Tableau : known for its advanced visualization capabilities and interactivity, with widespread adoption in sectors such as finance, healthcare, and retail;

• Qlik Sense stands out for its associative engine, which allows for freer and more exploratory analyses, with a strong focus on pattern discovery;
  
• Looker : a Google Cloud platform focused on more robust analytics and driven by centralized data models, with strong integration with BigQuery.
• Metabase offers an open-source alternative that stands out for its ease of use and accessibility. Unlike more enterprise-oriented solutions such as Power BI or Tableau, Metabase is designed to allow anyone on the team, even without in-depth technical knowledge, to explore data and create dashboards. Its intuitive interface allows you to translate complex information into clear and interactive visualizations. Ideal for promoting a decentralized data culture and empowering users to answer their own questions.

However, BI doesn't begin or end with just visualization tools. Other resources are also essential for a solid operation , such as:

• Data integration solutions (iPaaS) : such as Skyone Data , which connect different systems and allow data to flow in an automated and secure way;
  
• Modern data warehouses , such as Snowflake, Google BigQuery, or Amazon Redshift, centralize processed data ready for analysis.
  
• Governance and security layers : ensuring controlled access, traceability, and compliance with regulatory standards such as the General Data Protection Law (LGPD).

Ultimately, what differentiates a good BI operation is not the tool itself, but how well it fits into the company's reality , that is, its processes, challenges, and objectives.

In the next section, we'll see why all this is worthwhile: we'll discuss the concrete benefits that Business Intelligence can generate when well implemented.

Real benefits of Business Intelligence

Talking about data might seem too abstract for beginners. But Business Intelligence shows its value precisely when it moves beyond theory and starts solving everyday problems with clarity, focus, and agility.

According to BARC , companies that adopt BI make decisions up to 5 times faster than those without a data strategy . And this agility makes a difference in a market where responding first can mean winning or losing important opportunities.

See what can change in practice when data starts working in favor of the business:

• Faster and better-informed decisions : with accessible and organized data, teams gain the confidence to act. What previously depended on numerous meetings and assumptions is now resolved based on facts.
  
• A clearer view of company performance : BI shows where the company is doing well and where there are areas for concern, without relying on isolated reports or loose interpretations;
  
• Reducing waste and rework : by identifying patterns and bottlenecks, BI helps eliminate inefficiencies that cost time and money, whether in operations, customer service, or strategy;
  
• Alignment between teams and more connected decisions : when everyone has access to the same data, understanding is shared and goals become more tangible, which strengthens execution;
• The ability to anticipate trends and act proactively : BI allows you to observe market movements, consumer behavior, and seasonality. This helps you better prepare for what's to come, without playing catch-up.

All these benefits don't require large structures to get started: the most important thing is to take the first step with a clear strategy connected to what the business really needs.

But before moving forward, it's worth understanding what usually hinders this journey . Because recognizing the obstacles is the first step to overcoming them with more preparation. Check it out!

Common barriers and how to overcome them

Many companies want to make better use of their data, but in practice, they encounter obstacles that hinder their strategy before it even begins. And the most curious thing is that almost always, the problem isn't the tool itself, but rather how BI is understood, implemented, and used in daily operations .

Recognizing these barriers from the start helps build a more solid foundation, avoiding frustration and increasing the chances of success .

Below are some of the most frequent challenges and what can be done to overcome them:

• Too much data, but little confidence in the information : when systems don't communicate with each other, data is inconsistent or outdated, and no one knows which number is correct, BI loses credibility—even before it begins. To move forward , prioritize quality, not quantity. Start with a few reliable sources and organize the most strategic data for the business;
  
• A culture that still doesn't value data-driven decisions : in many companies, decisions are still made based on " gut feeling ." In this scenario, BI seems too bureaucratic or technical, which generates resistance. To move forward , demonstrate value with simple, useful examples that are relevant to daily operations. When BI solves a real problem, it becomes seen as an ally, not a complication.
• Lack of clarity about BI objectives : if the company doesn't know what it wants to answer with the data, any dashboard will seem confusing or unnecessary. To move forward , start by asking the right questions. "What do we need to understand better? What impacts our operation or customer today?". This provides focus and prevents BI from becoming just another pretty but hollow tool.
  

Recognizing these challenges doesn't mean halting the journey . On the contrary, it means facing it with more preparation, empathy, and focus on what truly matters.

Now that we've laid it all out, in the next section, we'll discuss how to structure the first steps in a practical and sustainable way, connecting data to your company's reality.

How do you start a BI strategy in your company?

After understanding the benefits and recognizing the challenges, the question naturally arises: "Now what? Where do I start?".

The good news is that a Business Intelligence doesn't need to start big to be effective . The most important thing is to start right, with focus, simplicity, and a view of the real business objectives.

More than just implementing tools, the secret lies in asking the right questions, involving the right people, and maintaining clarity about the impact you seek to generate. Below, we indicate the first steps for a safer and more consistent BI journey:

• Define a real problem to be solved with data : BI isn't about measuring everything, but about measuring what matters. Start by identifying a question the company needs to answer: "How can we improve sales forecasting? Where are we losing margin?". The clarity of the problem will guide everything else.
  
• Map where the data is located and how it arrives : it's worth understanding which systems the company uses today, how the data is recorded, and where there are gaps or rework. This diagnosis avoids surprises and shows what can be leveraged from the start;
  
• Choose simple and relevant indicators : focus on a few KPIs that make sense to those who will use the data. It's better to have three numbers that guide real actions than ten dashboards that nobody consults.
  
• Test, learn, and adjust : BI is an iterative process. Start small with a simple pilot that can be quickly validated. Use the learnings to adjust and gradually expand as maturity grows.
  
• Involve people from the start : the success of BI depends on people, not just systems. Include teams in the process, listen to those on the front lines, and translate the data to their reality. This increases engagement and prevents rejection.

With these steps, BI begins to take shape organically, connected to the reality of the business and focused on tangible results. But this is only the foundation: to evolve, it is necessary to keep up with how the use of data is transforming , and how new technologies and approaches are reshaping the role of intelligence in business.

That's what we explore next: the trends that are shaping the future of Business Intelligence and what your company can gain by anticipating this movement.

The future of BI: trends that will transform business intelligence

Like any technology, BI is not a finished product: it 's a constantly evolving field . As data gains even more relevance in business strategies, the role of Business Intelligence evolves, from supporting analysis to becoming a key player in decision-making.

Below, we highlight five trends that are already shaping the future of BI and that should impact companies of all sizes in the coming years:

• Business Intelligence (BI) with embedded artificial intelligence (AI) and machine learning (ML) : the combination of AI and ML with BI is changing the game. Instead of just analyzing what happened, companies are starting to predict scenarios, identify risks in advance, and even suggest actions. According to Coursera, this is one of the most transformative trends in current BI, especially for businesses seeking to gain speed and personalization in decision-making .

• Real-time data analysis is no longer a luxury but a necessity : with the digitization of processes, the timing of decisions has become as important as the decisions themselves. Platforms that operate with real-time data are already a reality and are helping companies react faster, based on events happening now, not weeks ago. Improvado shows that the adoption of real-time BI is among the most prioritized strategies by leading data companies .
  
• Interacting with data through natural language processing (NLP) : The use of Natural Language Processing (NLP) allows users to ask questions directly to the data, in common language, for example, "what was our net margin in the last quarter?". This reduces dependence on analysts and makes BI accessible to all teams. Synoptek highlights this trend as an essential step towards democratizing the strategic use of data .
  
• Data-driven culture as the foundation of operations : the BI of the future will not be a department, but a culture. Marketing , sales, operations, and customer service teams need to operate with data at the center of their decisions. Keyrus points out that companies with a data-driven culture are 23 times more likely to acquire customers and 19 times more likely to be profitable .
  
• Governance and security become structural : with the increasing sensitivity and volume of data, governance is shifting from "best practice" to a mandatory pillar. BARC highlights that mature BI organizations are prioritizing clear models of access, accountability, and security to ensure consistency and trust in the data used .

These trends don't just point to a more technological future: they reveal a shift in mindset . Business Intelligence (BI) is ceasing to be a resource "for the few" and becoming an essential organizational competency, as strategic as finance or operations themselves.

And this transformation is already within reach of companies seeking greater agility, autonomy, and practical intelligence for their daily operations. With the right data, well-connected and organized, it's possible to make faster, more sustainable decisions aligned with what truly matters.

Below, we want to tell you how Skyone makes this possible, simplifying access to intelligence and connecting dispersed data to generate real business value!

Skyone: How we connect scattered data to generate actionable intelligence

Transforming data into strategic decisions can seem like a complex journey—and often it is. But it doesn't have to be a lonely one .

At Skyone , we believe that clarity is born from the right connection —between systems, between areas, between data that previously lived in silos, isolated. Our platform was created to do just that: integrate, organize, and deliver intelligence where it truly makes a difference, which is at the moment of decision.

This means moving away from "report hunting" mode and entering a new rhythm , where the right data appears at the right time, in the way each area needs it. And this applies both to those who are starting out and to companies that want to scale their data maturity.

If you feel like you're swimming in data but still lack direction, perhaps it's time to redirect your compass. We want to help your company turn that key , with ease, security, and focus on what matters.

Talk to a Skyone specialist today and take advantage of the experience of those who have already helped hundreds of businesses make smarter decisions every day!

Conclusion

If you've made it this far, you've already realized: Business Intelligence isn't about having more data, but rather about having more clarity about that data.

More clarity to know what's working, what needs adjustment, and where the real opportunities lie . More clarity to make decisions that don't depend on guesswork, but on facts, context, and a vision for the future.

Throughout this content, we've opened up the game of BI : we've shown how it works in practice and why it can be a game-changer for companies of all sizes. And, most importantly, we've reinforced that you can start now , with what you already have, focusing on what really matters.

Because BI isn't about having a robust structure from the beginning. It's about asking good questions , connecting the essentials , and creating the habit of deciding based on what the data reveals . The rest is evolution!

If this content helped you better understand what BI is, how about continuing to explore with us? We have much more to share. Visit and read other articles on our blog !

FAQ: Frequently Asked Questions about Business Intelligence

Business Intelligence (BI) may seem like an overly technical topic until you realize it's behind faster, more efficient, and accurate decisions in companies.

If you're starting to explore this world, it's natural to have questions. Therefore, we've compiled the most common questions about BI here, with straightforward answers to help you understand the essentials and take your first steps with more confidence.

What is Business Intelligence (BI) and why is it important?

Business Intelligence (BI) is the set of processes, tools, and practices that transform raw data into useful information to support strategic decisions. It is important because it allows for a clearer understanding of business performance, identifying problems before they worsen, and finding opportunities that might otherwise go unnoticed.

In a competitive market, BI helps make decisions with more confidence, less guesswork, and greater agility.

What is the difference between Business Intelligence (BI) and Business Analytics (BA)?

Both are part of the same data journey, but operate at different stages:

• Business Intelligence (BI): organizes and presents past and present data, offering clear visibility into what is happening in the company. It focuses on monitoring and understanding the present.
  
• Business Analytics (BA) goes further, using statistical techniques and predictive models to identify patterns and forecast future scenarios. It focuses on explaining and anticipating what might happen.

In short, BI helps us understand the present; BA helps us prepare for the future.

How do I start a BI strategy in my company?

The first step is simple: start with a real problem that needs solving. Avoid thinking of BI as a complex and technical project. Then, define an important business question, identify where the data that helps answer it is located, and choose tools that fit your reality.

With this, it's possible to start small, test, learn, and expand gradually—always focusing on the clarity and usefulness of the information for decision-makers.

Written by Skyone