Spatial Analysis of the Age of Condominiums in São Paulo as a Strategic Tool for Administrators

doi:10.22167/2675-6528-202603365

Article

October 16, 2026

Spatial Analysis of the Age of Condominiums in São Paulo as a Strategic Tool for Administrators

Spatial Analysis of the Age of Condominiums in São Paulo as a Strategic Tool for Administrators

Peterson Augusto Ferreira; Lauro Marques Vicari

DOI: 10.22167/2675-6528-202603365

Article derived from a Course Conclusion Work (TCC), with content based on the student’s original work and adapted to the editorial format of the E&S Magazine with the support of the ResumeAI tool, an artificial intelligence solution developed by Instituto Pecege for textual synthesis and organization.

Summary

The housing densification in São Paulo, where 29.4% of the population resides in apartments, has established a highly competitive condominium management market that demands spatial data-based prospecting strategies. The study aimed to map the urban evolution of the São Paulo capital through spatial analysis algorithms and building age indicators for the development of competitive intelligence tools. The methodology comprised the extraction and integration of public CNPJ data via the KNIME platform, resulting in a database of 32,040 condominiums, 98% of which were geocoded with the Google Maps API. Macro-spatial analysis identified that the East and South Zones led recent real estate growth, while peaks in registrations in 1984 and 1985 were associated with changes in tax legislation and not with real construction cycles. In parallel, micro-spatial analysis used the BallTree algorithm to compare each condominium with its 20 nearest neighbors, revealing that 29% of the units represented points of local renewal in consolidated areas. The results were consolidated in an interactive dashboard that allows strategic visualization of the market at different levels of granularity. It was concluded that the integration of data science to the territory allowed administrators to replace generic approaches with personalized prospecting tailored to the lifecycle and competitive reality of each condominium, optimizing the allocation of marketing resources and the effectiveness of sales teams.

Keywords: BallTree Algorithm; Spatial Analysis; Urban Data Science; Condominium Management.

1. Introduction

The city of São Paulo, the largest metropolis in Latin America, has experienced a continuous process of verticalization over the past decades. This phenomenon has significantly transformed the urban landscape and social dynamics. According to data from the 2022 Demographic Census of the Brazilian Institute of Geography and Statistics, approximately 3.34 million people reside in apartments in the São Paulo capital, which corresponds to 29.4% of the population. This number represents a notable increase compared to 2010, when 2.59 million people (24.5%) lived in vertical units (IBGE, 2022). This movement is driven by real estate appreciation, population densification, and public policies that, at different times, encouraged the construction of buildings in specific areas of the city (Bonduki, 2024; Nakabashi; Kahtalian, 2023).

The verticalization in São Paulo has a complex history that shaped the current configuration of the metropolis. In the 1950s, the first buildings were concentrated in central regions, such as República, Bela Vista, and Higienópolis, attracting middle-class residents and immigrants seeking proximity to work (Somekh, 2015). In the 1960s and 1970s, the expansion extended to neighborhoods like Moema, Perdizes, and Vila Mariana, driven by the construction of major avenues and the growth of public transportation (Santos, 2020; Cunha, 2024). In the 1980s and 1990s, verticalization intensified in more distant areas, such as Tatuapé and Santana, following real estate appreciation and the arrival of shopping centers (Bonduki, 2024; Santos, 2020). From the 2000s onwards, the transformation became even more evident in high-end neighborhoods, such as Vila Olímpia, Itaim Bibi, and Vila Nova Conceição, which began to concentrate large residential and commercial towers. Simultaneously, peripheral neighborhoods also registered an increase in the number of buildings, often associated with housing programs or more popular-standard developments, revealing the unequal distribution of verticalization in the São Paulo territory (Albuquerque, 2010).

This densification process directly impacts urban infrastructure, straining public transportation and demanding continuous investments in sanitation, electricity, and basic services. Regions like Pinheiros and Vila Madalena, despite having good infrastructure, face challenges related to mobility and cost of living (França; Almeida, 2018). The environmental impact is also significant, with densification in areas such as Vila Mariana and Brooklin contributing to the formation of heat islands and increased soil impermeabilization (Navarro, 2018). Furthermore, the concentration of buildings in flood-prone regions, like the Tietê River floodplain, amplifies the risks of flooding (Maglio, 2008). From a social perspective, verticalization has altered the demographic profile of neighborhoods like Saúde, Lapa, and Ipiranga, with the replacement of horizontal constructions by buildings attracting young professionals and investors (Rolnik, 2015; Fix, 2007).

In this scenario, the age of condominiums emerges as a relevant indicator for understanding the city’s dynamics. Recent condominiums reflect regions undergoing full real estate expansion, while intermediate buildings indicate transition zones with gradual urban renewal. Older condominiums, in turn, reveal consolidated areas, where preservation or a slow pace of real estate replacement play a central role (Silva, 2020). The temporal analysis of condominium distribution allows for the identification of growth trends and an understanding of how different regions face pressures and challenges, providing crucial information for public authorities in housing planning and for the private sector in assessing investment risks and opportunities (Somekh, 2015).

Understanding the distribution and age of buildings is fundamental not only for the study of urban dynamics but also for interpreting the functioning of the real estate market and condominium management. In a highly verticalized city like São Paulo, thousands of residential condominiums demand administration, maintenance, and financial management services, creating a competitive environment among management companies. In this context, identifying regions with different real estate profiles helps companies in the sector better understand the territory in which they operate. Neighborhoods with older buildings may present distinct demands compared to more recent condominiums, while areas with a great diversity of construction ages may indicate processes of urban renewal or transformation of the local real estate market. The absence of competitive intelligence tools that integrate spatial and age data of condominiums represents a practical gap for management companies, which often use generic prospecting approaches.

Given this context, the objective of this study is to map the urban evolution of São Paulo through spatial analysis algorithms and building age indicators. The identification of these patterns aims at the development of competitive intelligence tools to optimize prospecting and marketing in the condominium management sector.

2. Material and Methods

The study adopted an applied research approach to map the urban evolution of São Paulo, using spatial analysis algorithms and building age indicators. The objective was to develop competitive intelligence tools to optimize prospecting and marketing in the condominium management sector. The city of São Paulo was the unit of analysis, focusing on residential and commercial condominiums.

The data collection was based on secondary information from the National Corporate Taxpayer(s) Registration (CNPJ), made available by the Federal Revenue of Brazil (Dados Cnpjs, 2025). Condominiums were defined as legal entities registered under the nature of condominium buildings, identified by CNAE 8112-5/00, covering vertical and horizontal units.

The KNIME platform (KNIME, 2025) was used to build an automated “pipeline” for data extraction, transformation, and loading (ETL). The process included iterative reading of CSV files, filtering of São Paulo matrix CNPJs with CNAE 8112500, integration of company and establishment data, and export to a final table. The initial dataset contained 32,040 condominium records.

The geocoding of condominium addresses was performed using the Google Maps API, via Python scripts. Complete addresses (street, number, neighborhood, city, state, and ZIP code) were sent to the API to obtain geographic coordinates of latitude and longitude. The procedure was executed gradually, respecting the platform’s request limits.

After geocoding, inconsistencies were visually verified and corrected. Approximately 500 records without valid coordinates were excluded. The final database for spatial analysis contained approximately 31,500 geocoded condominiums (98% of the total). The variables included company name, administration start date, address, and geographic coordinates.

The age of the condominiums was determined by the CNPJ opening date, the official record of the start of operational activities. Chronological age (IE) was calculated by the difference between the current year (AA) and the year of legal registration (AC), according to IE = AA – AC. This variable was used as consistent public data for large-scale analyses.

The regional classification of condominiums into administrative zones used the official cartographic base of the municipality of São Paulo, obtained from the GeoSampa portal (Portal GeoSampa, 2025). KML files of the administrative divisions (north, south, east, west, and central zones) were extracted. The procedure consisted of overlaying the geocoded points onto the polygons of the municipal zones, identifying the region of each condominium.

The microspatial analysis, focused on the immediate neighborhood, employed the BallTree algorithm, implemented in Python via the Scikit-learn library (Scikit-learn, 2026). This algorithm organizes space into hierarchical circular regions, optimizing the search for nearby neighbors. The BallTree was configured with k=20, comparing each condominium to its 20 closest geographic neighbors, using Euclidean distance.

The ages of the condominiums were segmented into quartiles calculated internally for each local neighborhood grouping. Based on these quartiles, the units were classified into three categories: “Local Renewal” (age below the first quartile), “Locally Old” (age above the third quartile), and “Surrounding Standard” (age between the first and third quartile).

In the macro-spatial analysis, neighborhoods were the study units. Buildings were classified into age groups: new (up to 10 years), intermediate (11 to 49 years, subdivided into 11 to 20, 21 to 35, and 36 to 49 years), and old (50 years or more). The 50-year limit for “old” was based on real estate appraisal studies (Silva, 2020).

For data visualization and interactivity, an interactive “dashboard” was developed. This tool allowed the exploration of over 32,000 condominium records at different levels of granularity, distinguishing between micro and macro-spatial analyses. The dashboard consolidated information to support strategic prospecting and marketing decisions in the condominium management sector, with dynamic filters by neighborhood and name.

3. Results and Discussion

The analysis of the collected data revealed significant patterns in the urban evolution of São Paulo and in the distribution of condominium stock, providing subsidies for the development of competitive intelligence tools. The initial database, composed of 32,040 condominiums registered in the National Corporate Taxpayer(s) Registration (CNPJ), underwent a rigorous geocoding process. Approximately 500 records could not be geocoded due to inconsistencies in the addresses, such as the absence of street names or generic denominations, resulting in a final base of about 31,500 condominiums with valid geographic coordinates, representing 98% of the original base. The age of the condominiums was determined by the CNPJ opening date, an official indicator that, although it may not exactly correspond to the physical completion of the work, offers a consistent metric for large-scale analyses.

The age distribution of condominiums in the city of São Paulo demonstrated marked heterogeneity, reflecting the diverse construction and verticalization cycles that have shaped the metropolis over time. This diversity highlights the importance of analytical approaches at multiple scales, both macro-spatial, to identify regional trends, and micro-spatial, to understand neighborhood dynamics. The analysis of condominium distribution by geographic zone and age range revealed that the South Zone concentrates the largest number of records, with 12,191 condominiums, and shows a predominance of buildings with intermediate ages, between 21 and 49 years, indicating an intense verticalization process that occurred in the last decades of the 20th century.

The East Zone emerged as the second region with the largest volume of condominiums, totaling 7,348 registrations, and stood out for a relatively higher proportion of more recent buildings, up to 10 years old. This profile suggests that the region has been the stage for more recent real estate expansion processes. In contrast, the Central Zone, with 5,130 condominiums, exhibited a predominance of buildings in the intermediate and advanced age ranges, a pattern that aligns with the older occupation history of this area of the city, where verticalization began in earlier phases of urban development.

The West Zone, with 4,724 records, showed a relatively balanced age distribution among different bands, indicating the coexistence of buildings constructed in various periods. The North Zone, in turn, registered the lowest number of condominiums in the analyzed database, with 2,643 units, but also showed a significant proportion of more recent constructions. In general, a considerable portion of the city’s vertical real estate stock is concentrated in the intermediate age bands, especially between 21 and 49 years old, which points to intense urban expansion cycles in recent decades, as observed by Somekh (2015).

The temporal analysis of building construction, visualized through the distribution of the registration year, indicated that the median construction year is approximately between the late 1980s and early 1990s in all zones. This finding suggests a period of intense verticalization in the city. Although all zones show a similar range, with buildings dating from the 1950s to more recent constructions, the North and East Zones exhibited slightly more recent medians, which may indicate a higher intensity of construction in more recent periods. The absence of “outliers” at the ends of the whiskers demonstrated that there are no buildings with isolated ages that drastically deviate from the regional pattern, confirming a relatively homogeneous distribution of the verticalization process.

Macrospatial Analysis

The macro-spatial analysis was consolidated into an interactive panel that allowed the visualization of the condominiums’ maturation profile by neighborhood. The buildings were categorized into five age groups: new (up to 10 years), early intermediate (11 to 20 years), consolidated intermediate (21 to 35 years), advanced intermediate (36 to 49 years), and old (50 years or more). This classification, based on real estate appraisal studies that consider 50 years as a reference for useful life (Silva, 2020), allowed for the identification of the predominant profile of each locality. For example, in Jardim Paulista, 65% of the buildings fall into the advanced intermediate range, while in Santana, the highest concentration is in the consolidated intermediate profile, providing input for targeted marketing strategies.

The monitoring of the volume of annual registrations revealed two atypical historical peaks: 3,479 registrations in 1985 and 1,258 in 1984. These massive volumes did not reflect actual construction cycles, but rather a change in the Brazilian tax legislation of the time, which established the mandatory registration of condominiums in the former CGC (current CNPJ) for the purpose of formalizing employees and withholding taxes. This administrative backlog led to the simultaneous regularization of thousands of existing condominiums, such as those found in Jardim Paulista and Bela Vista, distorting the perception of real growth in the real estate stock.

In contrast to administrative peaks, the period from 2019 onwards demonstrated real and consistent real estate growth, with volumes exceeding 760 annual registrations in 2022, 2023, and 2024. This growth trend, although it showed a decline in 2025, reflects a market dynamic based on the construction of new properties. The distinction between administrative peaks and real growth is crucial for an accurate interpretation of urban evolution and to prevent condominium administrators from basing their strategies on distorted data.

The geographic distribution of new registrations by zone, between 2019 and 2025, showed that the East and South Zones consistently led the volume of condominium deliveries. In 2022, for example, the East Zone registered 332 new condominiums, while the South Zone registered 210 units. The North Zone maintained stable growth, with its highest volume of deliveries in 2023, totaling 128 units. The West Zone demonstrated a more recent acceleration, reaching its peak of 114 new condominiums in 2024, while the Central Zone presented the lowest absolute volume, with an average of approximately 40 units per year.

This integrated analysis confirmed that urban renewal in São Paulo occurs more intensely from the “peripheries to the center” in terms of new construction volume. The East and South Zones acted as the main drivers of recent real estate growth, while the other zones maintained specific expansion rhythms. Visualizing this data on a historical condominium map allowed for geographical validation of these trends, showing how urban densification behaved in each zone over the years and where the new growth vectors are consolidating.

The ranking of condominiums by neighborhoods, which presents the absolute number of units in descending order, identified the main poles of verticalization in the city. Neighborhoods with a strong real estate tradition, such as Jardim Paulista (917), Pinheiros (913), and Vila Mariana (892), lead the total volume of condominiums. This visualization is fundamental to understanding the density of each neighborhood and to identifying new rising neighborhoods, such as Itaquera (347) and Tatuapé (402), which are climbing positions in the ranking. This quantitative analysis is essential to validate whether neighborhoods with a higher volume of buildings also concentrate the largest market for condominium services and maintenance, guiding the allocation of marketing resources.

Microspatial Analysis

The application of the BallTree algorithm, with the parameter k=20 to identify the nearest neighbors and segmentation by age quartiles, allowed each condominium to be classified in relation to its immediate surroundings. This micro-spatial approach revealed specific urban renewal patterns that would be imperceptible in aggregated analyses of entire neighborhoods. The results indicated that 42% (13,280 units) of condominiums in São Paulo city fall into the “Surrounding Pattern”, meaning their age is aligned with the predominant age in the immediate neighborhood.

Significant portions of the condominium stock, however, broke this pattern. It was found that 29% (9,047 units) were classified as “Local Renewal”, indicating significantly newer buildings than their 20 direct neighbors. In parallel, another 29% (9,265 units) were classified as “Locally Old”, representing buildings older than the third quartile of their neighbors. This distribution demonstrates a balanced coexistence between new, old, and standardized buildings, and confirms that urban renewal occurs in a dispersed manner, block by block, requiring an analytical look directed at each unit.

The “Condominium Analysis in Relation to its Surroundings” interface functions as a strategic tool for the commercial department of condominium administrators, transforming raw data into personalized sales arguments. By identifying a building classified as “Local Renovation”, sales representatives can visualize newer buildings than the street average, focusing on technological facilities. On the other hand, “Locally Old” buildings, such as the Lilian Building (1969), can be targeted for infrastructure or structural modernization services and building inspections, based on the actual needs of the edifice. This approach allows administrators to abandon generic prospecting and adopt personalized tactics, optimizing the sales team’s time and ensuring that the solution presented to the building manager is aligned with the building’s lifecycle and competitive reality.

In summary, the research demonstrated that the integration of data science with spatial analysis and building age indicators is fundamental to understanding the urban dynamics of São Paulo and developing competitive intelligence tools. The macro-spatial findings revealed patterns of growth and aging by zone and neighborhood, while the micro-spatial analysis identified dynamics of renewal and consolidation at the neighborhood level. These results allow condominium administrators to replace generic approaches with personalized prospecting, optimizing the allocation of marketing resources and the effectiveness of sales teams, by directing specific campaigns based on the aging profile and competitive reality of each condominium.

4. Conclusion

This study aimed to map the urban evolution of São Paulo through spatial analysis algorithms and building age indicators, seeking to develop competitive intelligence tools for the condominium management sector. It was found that the city of São Paulo exhibits a spatially heterogeneous verticalization phenomenon, where the age of buildings acts as a crucial indicator of urban dynamics. Macro-spatial analysis identified that the East and South Zones led recent real estate growth, with a significant volume of new condominiums delivered between 2019 and 2024. It was observed that peaks in registrations in 1984 and 1985 resulted from changes in tax legislation, not from real construction cycles, distinguishing administrative from real estate growth. At the micro-spatial level, the application of the BallTree algorithm revealed that 29% of condominiums represented points of local renewal, being significantly newer than their direct neighbors, while another 29% were classified as locally old. This granularity demonstrated that urban renewal occurs in a dispersed manner, block by block. The study’s main contribution lies in the integration of data science to the territory, allowing condominium administrators to replace generic approaches with personalized prospecting, aligned with the life cycle and competitive reality of each building, optimizing the allocation of marketing resources and the effectiveness of sales teams.

Despite the methodology’s effectiveness in processing over 31,500 valid records, some limitations were identified, such as possible discrepancies between the CNPJ opening date and the physical completion of the work, as well as geocoding errors for a small portion of the records. However, the methodology ensured high representativeness of the São Paulo territory. The results were consolidated into an interactive dashboard, offering immediate practical applicability for condominium administrators, transforming raw data into personalized sales arguments and targeted marketing strategies. For future studies, it is suggested to validate the effectiveness of these marketing and prospecting actions with the target audience, as well as to explore other data sources to refine building age and deepen the understanding of urban renewal dynamics in specific areas of the city.

Bibliographic References

Bonduki, N. 2024. O adensamento populacional é necessário, mas… Estudos Avançados 38(109): 1-16. Disponível em: https://www.scielo.br/j/ea/a/sfQYHrXtMhX6kvfHJW6ZG6n/. Acesso em: 20 set. 2025.

IBGE. 2022. Censo Demográfico 2022. IBGE, Rio de Janeiro, Brasil. Disponível em: https://www.ibge.gov.br. Acesso em: 26 ago. 2025.

Nakabashi, L.; Kahtalian, M. 2023. Fatores relacionados à verticalização residencial nos municípios brasileiros. Ipea, Brasília, Brasil. Disponível em: https://repositorio.ipea.gov.br/bitstreams/b068621f-547b-4a28-86f9-c597a26cded8/download. Acesso em: 20 set. 2025.

Somekh, N. 2015. Evolução da verticalização em São Paulo e implicações para o planejamento urbano. Research, Society and Development 4(3). Disponível em: https://rsdjournal.org/index.php/rsd/article/download/247

Article originating from the Final Course Project of the Specialization in Data Science and Analytics of the MBA USP/Esalq

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The viability of a municipal early warning system for relevant drops in the Basic Education Development Index (Ideb) in elementary education (early and late years) in Brazilian municipalities was investigated. The study aimed to predict the probability of a relevant Ideb drop in the following cycle. For this purpose, lagged Ideb histories were combined with municipal fiscal and institutional indicators, such as Payment Capacity (CAPAG) and the Firjan Fiscal Management Index (IFGF), in addition to municipal spending on education. Historical data were used, with training in 2019 and 2021 and testing in 2023. Logistic regression, Random Forest, XGBoost, and LightGBM models were applied, evaluated by metrics such as AUC-ROC and AUC-PR. The results indicated that lagged educational variables had great explanatory power. The inclusion of fiscal variables showed heterogeneous gains and, in general, did not add predictive power to the models. Nonlinear algorithms, such as XGBoost and LightGBM, showed superior performance gains and stability over logistic regression, achieving AUC-ROC values of up to 0.805. The modeling proved more challenging for the early years of elementary education, with better performance in the later years. It was concluded that the proposal is empirically viable, especially for the later years, reinforcing the potential of using Machine Learning for timely monitoring and intervention in educational management.

Keywords: Education; Municipal management; Machine learning; Public policies; Predictive systems.

Artificial Intelligence

October 16, 2026

Why study if AI exists?

When answers become easy, learning comes to mean more than just arriving at them. Why do I need to learn this if I can ask an artificial intelligence? This type of question has accompanied education for decades. Why learn an operation if a calculator exists? Why memorize information if it can be found […]

Tax Management

October 15, 2026

Pink tax and the gender of price

How different marketing treatments for men and women are incorporated by consumption taxation Imagine a shelf on which two razors of the same brand and intended for the same purpose are displayed side by side: one has dark packaging and promises strength, precision, and efficiency; the other comes in shades of pink or […]

Health

October 13, 2026

The missing link in health transformation

Why is innovation not enough to drive changes in organizations and health systems Digital transformation has become a strategic priority for health systems worldwide. Electronic health records, artificial intelligence, telemedicine, remote monitoring, and data analysis are now part of the strategic agenda of governments and health organizations. Paradoxically, […]

Marketing

October 09, 2026

Bitcoin or pets: what Artificial Intelligence would not see

A real-life consumer intelligence case shows what gets left out of the brief A few years ago, an American insurance company hired a specialized consumer intelligence firm to answer three questions: The insurer was also considering launching paid insurance in bitcoin. At the time, the consultancy’s workflow was as follows: the analyst created a query […]

School Management

October 06, 2026

The school is not a casino: when trading cards become currency in the playground

Why, for certain students, does school manage to offer so few experiences of achievement? The World Cup is over. Brazil left the competition, the school holidays came, the final was played and the football calendar moved on. It would be reasonable to imagine that, with the end of the tournament and the return to classes, […] would also begin

Energy Transition

September 30, 2026

Renewable energies: the Brazilian advantage

Brazil needs to invest in the capacity to transform natural resources into innovation, productivity, and development. Talking about energy is talking about development. Behind industry, transportation, services, cities, and increasingly artificial intelligence, there is an energy infrastructure that sustains the economy. Understanding a country’s energy matrix is understanding […]

Data Analysis

September 30, 2026

When the data changes, has reality changed?

An analysis of almost 20 million teaching positions-year between 2020 and 2025 shows how changes in population composition and record production can alter the interpretation of historical series Between 2020 and 2025, the number of formal teaching employment positions identified in RAIS (Annual Relation of Social Information), from the Ministry of Labor, […]

Artificial Intelligence

September 28, 2026

Artificial intelligence and the trends

Why do so many people join in on the fun with ChatGPT? I was never the trend person. I still am not. Some pass through my timeline, I see them, I find them interesting but not to the point of trying them out. This was the case, inclusive, with some recent waves of images made by artificial intelligence, like the 80s trend, the one that […]

Project Management

September 25, 2026

AI accelerates answers; who makes the decisions?

The speed of technology only becomes an advantage when it is accompanied by the capacity to understand, verify, and assume responsibility for the results. Imagine a team that starts producing in an afternoon the analyses that previously required a week. The change seems to justify the investment in artificial intelligence. But, before counting the gain, it is worth asking who examined […]

Tax Management

September 01, 2026

Tax reform and estate planning in the countryside

Efficiency in managing taxes facilitates governance and allows for the organization of family succession. Rural wealth organization has become a strategic measure in light of the tax reform in Brazil, which came into effect this year. The planning of activities and rural wealth management, through tools such as the transition from an Individual to […]

Renata de Gaspari Valdejão Almeida

Artificial Intelligence

August 05, 2026

Inside the company and off the radar: the risks of Shadow AI

According to Microsoft, 75% of professionals already use artificial intelligence at work without company approval. The use of generative artificial intelligence is already part of the corporate routine. Tools like ChatGPT, Copilot, and other platforms help professionals produce texts, analyze data, create presentations, and accelerate tasks in practically all sectors. But this advance […]

Renata de Gaspari Valdejão Almeida

Strategy

July 02, 2026

The future as a competence

Academic interest reinforces the projection of scenarios as an essential tool for decision-making. While some companies are still trying to get the next step right, others are already working with multiple possible futures — and preparing for all of them. But after all, what does it mean to “think about the future”? Is it a trend, a strategy, or a new competence that […]

Renata de Gaspari Valdejão Almeida

Innovation

Technology

May 21, 2026

Agro SP Corridor: innovation, institutional articulation and future

Pecege commands the executive operation of the 400 km ecosystem activities that became known as the Brazilian agro Silicon Valley In 2025, in addition to taking over the management of the Piracicaba Technology Park, the Pecege Institute was also designated to command the executive operation of the State Agribusiness Innovation Corridor activities, the so-called […]

Education

April 27, 2026

How to turn a TCC into a business

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Technology

March 20, 2026

The human repertoire in the age of AI

Critical thinking and creativity are irreplaceable in the work of a marketing professional Artificial Intelligence (AI) is capable of incredible feats, but it does not yet possess the judgment, empathy, intuition, and strategic creativity necessary to do the job of a good marketing professional. In this area, it is important to know how to use the tool to automate […]

Renata de Gaspari Valdejão Almeida

Agribusiness

Innovation

February 23, 2026

ESG as a growth strategy in a cooperative in RS

Santa Clara balances social and environmental responsibility with innovation Founded in 1911 by Italian immigrants in Carlos Barbosa, in the Serra Gaúcha region, Cooperativa Santa Clara is an example that it is possible to balance economic growth with social and environmental responsibility. From a small cheese production company, the organization has evolved into a […]

Renata de Gaspari Valdejão Almeida

Agribusiness

Innovation

January 22, 2026

Brazil free of Foot-and-Mouth Disease: what changes for Brazilian beef?

With a herd of over 200 million head of cattle, the country is currently the leader in exports. Brazil recently received, for the first time, the certification of country free of foot -and-mouth disease without vaccination, conferred by the World Organisation for Animal Health (WOAH). The seal strengthens the country’s position as a reliable supplier of meat for the […]

Renata de Gaspari Valdejão Almeida

Innovation

December 09, 2025

Innovation: the new cycle of the Piracicaba Technology Park

Instituto Pecege assumes management, betting on the creation of new businesses Starting in 2026, Instituto Pecege will assume the management of the Piracicaba Technology Park (PTP). Among its responsibilities will be the administration, operation, maintenance, and expansion of the park, in addition to fostering activities in innovation, entrepreneurship, and science and technology. The choice was made […]

Renata de Gaspari Valdejão Almeida

July 06, 2026

Large-Scale Architecture: DSR-SCRUM Change Management

Mônica Alessandra Guerios; Maria do Carmo Assis Todorov Abstract generated by ResumeAI, an artificial intelligence solution developed by Instituto Pecege focused on synthesis and writing. Architecture and urbanism are configured as essential bases in an increasingly complex and challenging urban space, where the intrinsic connection between social, environmental, and technological issues […]