BI: complete business intelligence guide for you

If you have a company and have read or heard that a BI (read bi ai ) is the digital solution to organize everything and make it grow , but you don't know what it is, how to do it, where to start, or even if would really work in your case, then welcome to the wonderful world of business intelligence , or BI , which is its acronym.

This guide is for you to understand everything, from what business intelligence is and what it is for, why and how to have a BI , to the most used tools to compose all this business intelligence that will make your company grow, for sure. .

And if you still have any questions about business intelligence (BI) , we are always available and very accessible to help. So, just access us through one of our communication channels.

Now, enjoy this complete business intelligence guide that we have prepared for you.

What is BI (business intelligence)?

Let's start with the basics. Business intelligence or business intelligence is known worldwide by the acronym BI (as we said, in Brazil, it is pronounced bi ai ).

Initially, focusing on the term intelligence , it becomes easier for you to begin to understand that BI is not “something”, but rather a “set of things”.

And this is our starting point: what things?

Fundamentally, they are:

• people
• data
• Law Suit
• technologies
• tools
• systems
• organizational culture

All this complex intelligence is built in a way that is completely customizable for each company. This construction work is done by people who work in areas of data science and who do this by following processes through technologies using systems , tools and… Company data (from your company, for example).

And when all of this is working perfectly, it is clear that a new organizational culture has been successfully established.

What does that mean?

That company has developed an analytical mindset, that now it can finally be managed by those who make more assertive decisions , and that it has certainly grown because of this.

Business intelligence for analytical decision making

Despite being able to have a BI and so many technological advances, many companies still conduct business in a traditional and outdated way. And even though someone's experience is certainly a big differentiator, the preponderance of intuition in the digital age is inconceivable, right?

The issue with business intelligence is: with the large volume of information generated daily, every company can develop its analytical decision making.

In short: no more intuiting by looking at spreadsheets.

It's time to use data to understand customers, outline strategies and accelerate business results. It's no surprise that companies with advanced analytical capabilities have happier customers and are more productive, efficient and profitable .

So, the sooner decision makers wake up to using their own data to make all decisions, the sooner the company will reach what we call analytical maturity .

Don't know what this is?

This is when a business already has all the characteristics necessary to lead its market. The characteristics would be those “things” that we listed before.

Therefore, developing an analytical mindset is crucial for a company to be successful with its digital transformation .

And this has everything to do with business intelligence .

Using BI , strategic decision making will be guided by reliable data and information, helping your company to profit more , be more efficient , reduce risks and grow consistently. To do this, we emphasize that you need to eliminate intuition from your decisions.

And to finally be able to make analytical decisions, that is, decisions based on data, a process will take place (one of the “things” that make up BI ) until the transformation of data sources into intuitive visualizations, which we also call intelligent panels , dashboards or monitors .

Have you ever seen a dashboard before? Click here to view some models.

Business intelligence: what BI would look like in your company's day-to-day life

Using business intelligence masterfully implies being data driven , which is a great business opportunity. And it is a prerequisite for companies that aspire to leadership in their area of ​​activity.

You must want this for your business, right?

In everyday practice, a BI would work like this in your company: business intelligence would transform information from the past and present into illustrated reports ( smart panels ) that would facilitate analytical decision-making.

This is because the way you visualize data will be essential for you to avoid errors in data interpretation, which could result in bad decisions for your project.

To avoid this, using business intelligence , your company would start making decisions based on analyzed and very well interpreted data.

That's how it works.

With the use of BI , you and all interested people (stakeholders), such as analysts and decision makers, will all be able to manipulate and access data to conduct analyzes without needing the technical skills of a developer or data scientist . This means autonomy!

Attention: data without context has no value or meaning

So far, regarding what business intelligence is , is it clear that your company needs to put all the types of data it already has in a visual context that makes it easier to interpret so you can make decisions based on it?

Even simplifying this understanding, we also show that there is a set of “things” involved in a BI , which constitutes a complex system, but nothing that a company of any sector and of any size cannot achieve to truly grow with consistency. .

Therefore, a BI connects data with tools that place it in a clear, digestible, scannable and analyzable visual context by ordinary people, who are not experts in data analysis , but who, even so, can easily monitor the data. company performance and the identification of patterns, trends and anomalies in real time .

How to have a BI in your company

Now pay attention, because we are going to delve a little deeper into the content of our conversation.

For you to revolutionize your company, it needs to have a BI , and we explain that there are people, data, processes, technologies, tools, systems and organizational culture involved, right?

At each stage, a process is established.

And for you to start understanding this step by step, the path we follow to build a BI is basically this:

Business intelligence | ETAPA 1

This is the beginning of a winning data driven strategy . We will literally talk a lot with you and your team to map your company's entire past until we understand your current scenario and your needs. With this clear, it will be time to define which technologies will be used to achieve the goals that will be established.

Business intelligence | ETAPA 2

Map of the past ready! Clear goals! Now let's integrate all of your data sources and then transform and model this historical data. It's the beginning of building a solid foundation, in the cloud , to support all your company's data today, and after it grows.

Business intelligence | ETAPA 3

Finally, we will put our strategy into practice. With it, we will guide your company towards achieving the goals we established in the first stage. We will validate everything, test everything, document everything. And you will see excellent, automated reports so you can make the best decisions, in all areas, and make your company evolve.

How to transform historical data into tangible information?

To talk about this, let's dive a little deeper into step 2 now.

The transformation of large volumes of historical data is done through data extraction, transformation and storage (ELT) and data warehouse processes , as the figure below shows.

With the organization of the past being resolved by ELT and DW , BI finally comes into play, placing a layer of intelligence on top of organized data . This intelligence translates into interactive visual representations for real-time analysis and decision making.

So much so that, here at Indicium , we say that implementing BI is neither the beginning nor the end of a data project: it is about the present . It is a fundamental step that paves the way for organizations to explore the next step of analytical advantage , the future .

Business intelligence vs data analytics : different concepts

We can already say that a BI is a visualization tool that places a company's data in a simple and accessible context for future analysis. Its purpose is simply to identify a business question, seek relevant data to answer it in a convincing way for stakeholders to make decisions.

Alone, a BI only performs descriptive analyzes illustrating the information retained in the repositories through visualizations, such as graphs, tables, maps, etc.

Data analytics , in turn, goes beyond this, as it conducts investigative analyzes using applied data intelligence to prepare predictions about the future of companies.

In this context, BI and data analytics are complementary concepts. While BI provides the graphical representation necessary for business analysis , data analytics delves into data modeling and analysis techniques to obtain deeper insights into the future of organizations.

How do you know if a BI is the right solution for your company?

We have created a very simple path for you to discover whether BI implementation is suitable for your company. Just answer the following three questions.

1. Do you have difficulty accessing information about your company?

2. Do the reports you need take a long time to reach your desk?

3. Would you like to have more information to make business decisions?

RESULT

If your answer is yes to any of the three questions, then BI will be an interesting and suitable alternative for you to leverage your company.

Why should your company have a BI?

For the same reason that all companies should have. To quickly identify business problems in any area and be able to seek solutions in real time to resolve them.

In any area, it means that all sales, financial, production, human resources, logistics, service, marketing, quality, etc. problems are addressed. will be mapped.

We can say that, using BI , your company will have recorded a true astral map with information from the past and present, and the future beautifully predicted and planned for you to actually achieve the predictions (the established goals!).

It's not magic. It's science. It's cutting edge technology. It's constant innovation. Are given. And they are people, of course!

We are in the era of industry 4.0 , or the fourth industrial revolution , have you heard?

So, your company must have a BI because it is the right time for it.

This is the time for you to start using business intelligence and let it work for you, quickly and efficiently, in order to identify business problems in advance and avoid damage and losses to your company.

Want more why?

• Reduce costs.
• Be assertive in decisions.
• Produce more and better.
• Minimize risks.
• Optimize your business performance.

What are the tools for business intelligence?

We previously spoke superficially about data warehouse , also well known by its acronym DW .

Now, for you to advance your understanding of how to have a BI , know that a DW will be part of it. And regarding business intelligence tools , that's where we'll start.

Data warehouse: your BI database

A data warehouse is a database optimized for fast analytical queries of a large volume stored in it.

If you think that DW is something new, know that it is not. It has existed since the early 1990s and, since then, it has wonderfully allowed us to centralize data from different sources within a company to have a single source of truth .

To be clearer, we can say that the data warehouse (DW) is the house of data : a secure place that stores and integrates structured data in one place.

After all, data from different sources and formats do not integrate naturally. So, the great advantage of a data warehouse is precisely this consolidation of data from different information sources, such as operational systems, spreadsheets and CRMs, in a centralized location.

This is how DW transforms data into tangible information for decision-making by managers.

What is the function of a data warehouse?

A DW allows the analysis of large amounts of data at once, much faster than traditional databases. There are numerous features for a business, including:

1. consultation and reports: informs everything that has happened so far.
2. business analysis (OLAP): informs why any of these events occurred.
3. data mining: indicates what could happen and other relevant information.
4. dashboards and scorecards: clarify the present and monitor a company's performance, in accordance with business strategies.

And for your data warehouse to have all these functions, know that the operationalization of each of them requires different technologies , processes and conditions .

Implementation of a data warehouse

The idea of ​​visualizing your company's data in real time sounds incredible, doesn't it?

However, using inaccurate data to make decisions is like “taking a shot in the dark”. Therefore, for the data to reflect the reality of your organization, you first need to organize your house.

And this can be done with the help of data architecture .

Here at Indicium, for example, our data architects plan DW solutions in a personalized way, considering the specific needs of our customers. Therefore, the process may vary depending on each project.

For you to understand better, the following figure illustrates, in a simplified way, the chain of implementing a data warehouse .

The process begins with the collection of data scattered across different sources.

Then, extraction and transformation takes place ( ELT , remember?), a phase responsible for filtering and organizing the most relevant information available.

From there, loading serves as an aid in the transition of all collected data to the data warehouse . Finally, with this information stored, the DW is ready to be used and generate value for companies.

And now, let's focus a little on the transformation process, which we have also explained superficially before, called ELT .

ELT or ETL?

Let's explain.

We already know that building an efficient data warehouse is a guarantee of success for a business intelligence project , right?

However, until recently, the ETL process (in Portuguese, extract, transform and load ) was the most used method in data projects. Today, modern companies have turned to another alternative, much more agile, scalable, flexible and economical, the ELT (in Portuguese, extract, load and transform ).

And from now on, we will tell you the reasons for this transition and why ELT may be the best option for your company.

Can a BI survive without a data warehouse?

Let's see...

The data lake tool has emerged as a promising way to deal with large volumes of structured and, mainly, unstructured data. It is a technology that allows modern companies to profoundly improve their BI.

But how does this work without a data warehouse as an intermediary?

1. In the data lake , data is extracted and loaded without much preparation or structuring.
2. Then, analysts identify the relevant data and transform it according to their analysis.
3. And, finally, they explore this data using business intelligence tools .

This way, the distance from extraction to analysis is shorter, saving time.

So the answer is yes, a BI survives without a data warehouse . In fact, a BI approach in a data lake represents a great victory, especially in terms of cost, time and effort savings.

All this without losing the performance and concurrency that end users demand. Which doesn't mean that DW is no longer necessary.

What is a data lake or data warehouse?

In fact, ELT (in Portuguese, extract, load and transform) is a process that allows BI analysis bypassing the data warehouse . Despite this, DW is not simply eliminated, much less replaced.

The question is: if it is possible to solve BI only with a data lake, why build a data warehouse ?

Simple! Because without it:

• the data will not be in a format suitable for reporting.
• the data remains of low quality.
• processing will take longer and, as a result, performance will decrease.
• the data will be dispersed across systems in different departments.
• historical information will be missing.

In other words, to analyze structured and more detailed business data , you need all the preparation and transformation that only a DW has. It is still used for critical business analysis on its core metrics, such as finance, CRM, ERP, among others.

For example, if management needs to see a weekly revenue dashboard or an in-depth analysis of revenue across all business units, the data needs to be organized and validated. This analysis example cannot be assembled from a data lake exclusively.

Why should you adopt a data lake for your BI?

Because, effectively, in-data-lake BI , as this new process is being called, provides an integration that meets the demands of companies to react immediately to the contingencies of the dynamic market in which we live.

Business intelligence: 8 BI tools you need to know

In fact, there are a multitude of business intelligence tools available on the market. Therefore, you need to research and get to know each one of them to finally find the one capable of meeting your company’s needs.

To help you, we selected 8 BI tools and compared the most relevant aspects of each of them.

What are business intelligence tools for?

We saw that business intelligence , or business intelligence , is the combination of processes, systems and tools that work together to translate data into intuitive visualizations , such as smart dashboards, dashboards and monitors.

There are countless benefits of BI tools , and we highlight these:

• increased operational efficiency
• identification of potential trends and business opportunities
• visualization, monitoring and optimization of performance indicators (KPIs)

And, below, we list the eight selected tools, which are recognized by the market and can be a good alternative to boost your business.

Let's go to them!

1. Power BI

Power BI is Microsoft 's business intelligence tool and one of the most economical on this list. It has excellent protection and governance protocols and is the best option for those who work intensively with Excel . Its performance, however, tends to be less satisfactory on very large data sets.

2. Metabase

The great advantage of Metabase is that, even though it is ideal for beginner users, the platform is also one of the best tools for executing more complex queries, as it allows the use of the SQL language and the handling of the integrated notebook editor.

It is also easy to use and has open source, making it more accessible for businesses of all sizes. To top it off, Metabase allows collaboration between different business teams, so different sectors can ask questions and learn from the data.

3. Table

If you want great, easy-to-share reports, Tableau is the best choice. This tool allows users to easily share analytics within their organization while maintaining tight control over access and permissions.

And because it is extremely focused on visual analysis, it is very easy to use by new users. But despite the benefits, Tableau has a high cost and, therefore, is not always the right choice for smaller companies or those with reduced budgets.

4. Qlikview

Qlikview is an associative engine that enables data discovery without the need to use query tools. This reduces the risk of data loss and inaccurate results.

Qlikview 's associative exploration feature is based on simple select and search functions that can be entered by end users of all experience levels. This makes it possible to view relevant company data from multiple angles and gain new insights easily.

5. Google Data Studio

Google Data Studio is the ideal tool especially for those who work with G Suite and other Google tools . After all, it has native integration with the company's solutions. This way, teams have more agility and practicality when integrating the software into their daily lives.

Additionally, Google Data Studio is completely web-based. With this, it is possible to work collaboratively, through visualizations and panels in real time. However, there is the limitation of downloading and sharing visualizations only in PDFs, and the variety of graphics is not as extensive as other tools on this list.

6. Six sense

If you and your team are not technology experts, the Sisense BI tool may be the best choice for your company or department. Considered one of the most user friendly among those analyzed in this post, it allows the management of voluminous and complex data in a collaborative way.

This way, anyone in your organization can handle, analyze and visualize business data , without the need for IT department involvement.

7. Looker

Looker is a web-based business intelligence platform, which uses LookML as its own programming language.

This tool is used to perform SQL queries on the platform, a functionality that is considered, at the same time, one of its greatest strengths and weaknesses. This is because, although it is a flexible and powerful data query language, it requires the contractor to have an IT or data team to access its full capabilities.

Another differentiator of Looker is that it operates primarily in the cloud , allowing data engineers to model and provide calculations for other applications, and can also be used to build analytical applications from scratch.

8. Mode Analytics

Mode Analytics is a collaborative analytics platform used to make data-driven decisions . It hosts a central repository of work and presents it to analysts in real time, allowing them to resolve issues without having to recreate the work first.

One of the standout features of Mode Analytics is that you can easily work collaboratively. You can let your entire organization explore and contribute to your reports by simply sharing your project link.

Invest in business intelligence: implement BI

Business intelligence tools offer great rewards to businesses, enabling more cohesive, stable, agile and predictable data management.

Now that you know the BI universe in more detail , start your digital transformation journey.

We help our customers in many ways. And we can help you implement BI in your business.

Discover our services

BI consultancy and implementation

Visualize metrics, recognize patterns in data, and make smart decisions with our BI dashboards.

Custom data apps

Create data driven applications. Our data-apps include simulation models, predictive models, image-based models, among others

Data pipeline

Organize and transform your data with our extract, transform, and load (ETL) services.

Data warehouse

Store data in a secure repository to create advanced BI and analytics solutions.

Data visualization

Turn your data into smart, easy-to-understand visualizations to monitor the metrics you want, in real time.

Report automation

Configure reports automatically to increase the quality of your insights and the efficiency of your team.

Start your BI project

You can do this now. We guarantee many benefits and great differences.

• Cost reduction.
• Assertiveness in decisions.
• More productivity.
• Risk mitigation.
• Performance optimization.
• Experienced teams.
• Customized BI solutions.

Get in touch with our team of consultants and let's start your Data Driven Journey and, consequently, the implementation of your BI .

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