Today BI tools for data-driven decisions in companies are becoming increasingly relevant.

In fact, the Business Intelligence market is growing at a nearly double-digit rate. It’s significantly transforming areas such as cloud adoption, advanced analytics, data-driven decision-making, and the Internet of Things (IoT):

• 54% of companies state that cloud BI is critical or very important to their current and future strategies;
• $26.9 billion – the global BI market CAGR in 2022 was 11.9%.

The evolution of BI platforms

Enterprise BI platforms are part of a mature and highly competitive market. BI has shifted from a back-office application supporting primarily non-client-focused and non-revenue-generating use cases to a key corporate asset for competitive differentiation. Business areas now recognize the importance of having data analysts on their teams who can explore data to support decision-making. Current cloud BI adoption is highest in Manufacturing (58%), Financial Services (40%), and Business Services (40%).

Moving forward

Emerging technologies like AI, Natural Language Processing (NLP), and IoT will significantly revolutionize BI architecture and user interfaces. BI platforms are rapidly moving toward the concept of full integration, with a strong growth of connectors/APIs for various platforms, enabling seamless embedding in other applications.

With the API economy, BI tools can leverage multiple solutions across internal and external corporate environments.

Cloud BI adoption is expected to grow across several sectors, with an increase in multi-cloud and hybrid architectures hosting BI platforms. Enhanced insights through augmented BI analytics are a strategic theme for data-driven companies, as they can lead to a better understanding of the business environment, provide insights, improve decision-making quality, and even integrate sophisticated AI models.

Augmented BI analytics represents the most advanced evolutionary step in Business Intelligence. It democratizes access to and advanced use of data, including advanced analytics, NLP, streaming analysis, dashboard embedding, and more.

Typical benefits achieved through BI solutions

• Decision-making: provide valuable information to support data-driven decisions, reducing the risk of poor choices;
• Business monitoring: enable the tracking and control of KPIs, allowing for impact analysis of actions over time.
• Understanding phenomena: allow users to dive into business data, performing ad hoc analyses across multiple dimensions with self-service BI;
• Autonomous and complex analysis: create the ability to use advanced analytics with diverse and complex data landscapes, enabling autonomous decisions.

Factors to address in a scalable BI solution

To deliver high-impact Business Intelligence solutions, it is essential to address topics related to data storage, transformation, and presentation properly:

• Business relevance: provide meaningful information to support the business, considering stakeholder needs through the design of user-centered dashboards;
• Data integration: connect to data sources, perform ETL processes to integrate data, and design a data model tailored to facilitate dashboard development and enhancement;
• Automation and consistency: increase consistency through automated data pipelines and dashboard updates, enabling employees to shift from low-value activities to supporting business growth;
• Scalability and responsiveness: design a solution prepared to handle data growth and the integration of new sources while maintaining low latency and being responsive and flexible for business users;
• Autonomy and Augmented Intelligence: enhance business analysis by enabling self-service BI and leveraging big data and advanced analytics features to gain insights through predictive analysis, NLP, and more.

Software update: market overview

BIP constantly monitors the technology market to stay up-to-date on the state-of-the-art BI tools. According to Gartner’s Magic Quadrant, Power BI, Tableau, and Qlik remain market leaders, with a strong trend toward market consolidation.
Gartner’s Magic Quadrant reflects the current state of the BI market. Despite its revolutionary role, Qlik faces stiff competition. Power BI and Tableau stand out for their adaptability and competitive pricing strategies. In 2019, Salesforce acquired Tableau, and Google acquired Looker, reinforcing the market consolidation trend.

Leading BI tools

In addition to their functionalities, leading BI platforms offer a wide range of architectural solutions and integrations to provide the necessary tools to leverage data-driven business strategies, enabling organizations to evolve and enhance their hardware.

Below, we highlight the top BI tools:

• Power BI is Microsoft’s BI solution, with its cloud service (Azure) being the preferred public cloud BI provider for businesses today. It offers a broad range of BI and analytics features through its Power BI suite. Power BI Desktop can be used as a standalone, on-premises option for individual users or through enterprise server solutions. Users of Power BI Dataflow, Datasets, and Query Editor can accelerate the development of data pipelines to support dashboard creation.
• Tableau provides a highly interactive and intuitive visual exploration experience, allowing business users to easily access, prepare, and analyze their data without coding. Tableau’s three main products include Tableau Desktop, Tableau Server, and Tableau Online (Tableau’s cloud-based offering).
• Qlik offers governed data discovery and analysis, either as a standalone application or integrated with other apps. Qlik provides a wide variety of architectural deployment solutions (Qlik as a Service, Qlik Server on Cloud, Qlik Server Enterprise) along with multiple connectors, add-ons, and a data marketplace to enhance app development.

Benefits of BI tools for data-driven decisions in companies: a map of leading BI platforms in the market

BI tools for data-driven decisions in companies: the complete scope of a Business Intelligence project

A Business Intelligence project involves several stages, from data ingestion to report generation. Let’s explore each of them:

1. Data Ingestion. It refers to activities related to data collection, which can be done directly from data sources through connectors (in simpler cases) or mediated by ETL procedures in sophisticated pipelines. ETL stands for Extraction, Transformation, and Load.
2. Data Storage. Depending on the architecture, the data can be stored in data warehouses (DWH), data lakes, within the BI platform itself, or even not stored at all, requiring periodic data extraction.
3. Data modeling. It’s the way data is organized to support dashboard preparation and should be designed according to business needs. The data model depends heavily on the current infrastructure and data types.
4. Data Security. Users are the most important stakeholders but also pose a potential threat to data security. Leading BI tools offer different types of products, such as desktop licenses, server, and SaaS options, which can impact security decisions.
5. Data Reporting. Creating dashboards using BI tools, which play a key role in presenting the output of complex algorithms, geospatial analysis, NLP (Natural Language Processing), and more. More mature BI architectures provide users with basic data knowledge (data literacy) and self-service BI features to enable ad hoc (on-demand) analysis.

Tools for BI data reporting

Consulting to transform data into actionable insights: driving growth and operational efficiency

Although the market already uses emerging technologies in BI interfaces, such as AI, Natural Language Processing, and IoT, some companies that grow too quickly struggle to keep up with the modernization of these processes.

These companies still rely on multiple Excel reports, decentralized data sources, and perform analyses with varying figures depending on the department that generated the report.
This was the case for one of BIP clients—a large company in the agribusiness sector—where we implemented customized dashboards across the entire operation. This solution allowed the company easy and instant access to relevant, real-time information, enabling agile, data-driven decision-making. In turn, this led to exponential growth and optimized operational efficiency.

The journey from customer centricity to BI factory

The project began with identifying the need for management reports to support data-driven decision-making. Through two prior projects on governance for the customer-centricity division and data foundation, BIP mapped out approximately 60 analyses, reflected in 24 Power BI dashboards that enabled the following:

• Accuracy and data-driven decisions: relevant, real-time information ensures more precise and strategic decisions.

• Opportunity detection and problem anticipation: data analysis helps identify growth opportunities and prevent issues before they impact the organization.

• Increased operational efficiency and cost reduction: optimized processes and more efficient decision-making lead to cost savings and higher productivity.

Number of analyses mapped by areas

The main objective was to provide managers with a unified platform to access metrics and key performance indicators in real-time, enabling faster and more accurate analysis of the company’s performance.

Agile approach for flexibility and adaptability

By adopting the Agile methodology, we carried out the necessary configuration activities and executed the dashboard development phase in 7 sprints, delivering incrementally with constant user feedback.

This approach provided:

• Transparency: constant tracking of the project’s progress and clear communication with stakeholders.

• Interaction: identification and correction of inconsistencies, along with fine-tuning according to user needs.

Development of detailed dashboards oriented toward data-driven decision-making

The dashboards were built through successive cycles of analysis, design, and development for each mapped business area. The detailed steps were:

1. Requirements gathering: immersion in the processes and reports of the selected area to understand the data, desired KPIs, user needs, and data source mapping with all stakeholders (end users, Engineering team, and BI Analysts);
2. Template – design: creation and validation of mock-ups (in Figma) for the dashboards, adhering to the company’s visual identity and illustrating all desirable and feasible KPIs based on the available data;
3. Data integration: collection and provisioning of the data needed for KPI development;
4. BI development: development of the dashboards in Power BI according to the approved mock-up, stakeholder validation with necessary adjustments, and publishing the dashboards in the company’s Workspace with access control considerations (RLS);
5. Documentation: delivery of technical documentation related to the published dashboard;

One of the challenges faced during the development process was that most users were not accustomed to using dashboards previously. To address this, the team applied UX (User Experience) techniques and created an intuitive template, simplifying navigation through the dashboards.

In addition, a user-friendly homepage was created, with all dashboards developed and organized by the company’s departments.

Efficient schedule for success

The project was completed in 20 weeks, initially using 2-week sprints, which were adjusted at the start of the project to 3-week durations, taking into account the client’s internal dependencies and the team’s delivery pace.

The project team was composed of BIP specialists and company professionals, who actively participated in all agile ceremonies, contributing to constant feedback and rapid redirection in collaboration with BIP whenever difficulties arose.

To ensure each sprint covered the complete panel construction cycle, we divided the cycle into 3 activity groups:

• Group A: Requirements gathering, Template/Design, and Data Integration;

• Group B: BI Development and Publication;

• Group C: Documentation.

Since there was interdependence between the groups, the team simultaneously focused on 3 areas/departments per sprint.

Results and positive impact: turning data into growth and efficiency for a data-driven culture

With the implementation of the dashboards developed by BIP, the agribusiness company now has access to a complete and transparent view of its data, enabling its managers to make more assertive, strategic, and fact-based decisions. This is the development of a new data-driven culture.

Consulting for data-driven decision-making: BIP xTech can help

BIP xTech specializes in technological solutions. We help clients better organize their data, provide insights, and enhance artificial intelligence-driven solutions.
Visit the BIP xTech page and explore our success stories.