I had the opportunity to attend the Gartner Data & Analytics Summit in São Paulo, Brazil, from March 25-27. The conference brought together industry leaders, experts, and practitioners to discuss the latest trends, strategies, and best practices in data and analytics. Brazil’s growing importance in the AI landscape was evident throughout the event, with many insightful presentations and discussions focusing on AI adoption and innovation.
One of the interesting talks I attended was delivered by Eduardo Cantero Gonçalves, a senior Data Analytics manager at Mercado Livre (MercadoLibre). Mercado Livre is a leading e-commerce and fintech company that has established itself as a dominant player in the Latin American market. With operations spanning 18 countries, including major economies such as Brazil, Argentina, Mexico, and Colombia, Mercado Livre has built a vast online commerce and payments ecosystem. The company’s strong market presence and extensive user base have positioned it as a leader in the region.
During his presentation, Gonçalves shared Mercado Livre’s remarkable journey in democratizing data and AI across the organization while fostering a strong data-driven culture. As AI continues to transform industries worldwide, Mercado Livre’s experience offers valuable lessons for organizations looking to harness the power of AI and build a data-driven culture.
In this article, we will explore the key takeaways from Gonçalves’s presentation, focusing on the company’s approach to data democratization, empowering non-technical users with low-code AI tools, and cultivating a data-driven mindset throughout the organization.
Mercado Livre’s Data Democratization Journey
Mercado Livre’s journey towards data democratization has been a transformative process that has reshaped the company’s approach to data and AI. Gonçalves emphasized the importance of transitioning from a centralized data environment to a decentralized one, enabling teams across the organization to access and leverage data for decision-making and innovation.
A key aspect of this transition was the development of in-house data tools. By creating their own tools, Mercado Livre was able to tailor solutions to their specific needs and ensure seamless integration with their existing systems. This approach not only provided greater flexibility but also fostered a sense of ownership and collaboration among teams.
One of the most significant milestones in Mercado Livre’s data democratization journey was the introduction of machine learning tools designed for both data scientists and business users. Gonçalves highlighted the importance of empowering non-technical users to harness the power of AI and ML without relying heavily on data science teams. By providing low-code tools and intuitive interfaces, Mercado Livre has enabled business users to experiment with AI and ML, driving innovation and efficiency across various departments.
The democratization of data and AI has had a profound impact on Mercado Livre’s operations and culture. It has fostered a more collaborative and data-driven environment, where teams can easily access and analyze data to inform their strategies and decision-making processes. This shift has not only improved operational efficiency but has also opened up new opportunities for growth and innovation.
Empowering Non-Technical Users with Low-Code AI Tools
One of the key highlights of Mercado Livre’s data democratization journey is their focus on empowering non-technical users with low-code AI tools. During his presentation, Gonçalves emphasized the importance of enabling business users to experiment with AI and machine learning without relying heavily on data science teams.
To achieve this, Mercado Livre developed an in-house tool called “Data Switch,” which serves as a single web portal for users to access all data-related tools, including query builders, dashboards, and machine learning tools. This centralized platform makes it easier for non-technical users to leverage AI and ML capabilities without needing extensive programming knowledge.
Gonçalves specifically mentioned that Mercado Livre introduced low-code machine learning tools to allow business users to run experiments independently. By providing intuitive interfaces and pre-built models, these tools enable domain experts to apply their knowledge and insights to AI-powered solutions. This approach not only democratizes AI but also accelerates innovation by allowing more people within the organization to contribute to AI initiatives.
The impact of empowering non-technical users with low-code AI tools has been significant for Mercado Livre. Gonçalves noted that the company saw a substantial increase in the number of active users, data storage, ETL jobs, and dashboards following the introduction of these tools.
Mercado Livre’s success in this area serves as a valuable case study for other organizations looking to democratize AI and empower their workforce. By investing in low-code AI tools and providing the necessary training and support, companies can unlock the potential of their non-technical users and foster a culture of innovation.
Fostering a Data-Driven Culture
In addition to democratizing data and AI tools, Mercado Livre recognized the importance of fostering a data-driven culture throughout the organization. Gonçalves highlighted several key initiatives that the company undertook to cultivate a mindset that embraces data and AI-driven decision-making.
One notable step was the creation of a dedicated Data Culture area within Mercado Livre. This team was tasked with promoting data literacy, providing training, and supporting data-driven initiatives across the organization.
To measure the success of their data culture efforts, Mercado Livre developed a “Data Driven Index” that tracks user engagement with data tools. This index provides a quantitative measure of how well employees are adopting and leveraging data in their daily work. By regularly monitoring this index, the company can identify areas for improvement and adjust their strategies accordingly.
Another key initiative was the “Data Champions” program, which aimed to train advanced users who could then help multiply the data-driven culture throughout the organization. These champions serve as advocates and mentors, promoting best practices and assisting their colleagues in leveraging data and AI tools effectively. By empowering a network of champions, Mercado Livre was able to scale its data culture efforts and drive adoption across the company.
Lessons Learned from Mercado Livre’s Experience
Mercado Livre’s journey in democratizing data and AI offers valuable lessons for other organizations looking to embark on a similar path. One of the key takeaways from Gonçalves’s presentation was the importance of executive sponsorship in promoting a data-driven culture. Having strong support and advocacy from leadership is critical in driving organizational change and ensuring that data and AI initiatives are given the necessary resources and priority.
Another important lesson is the value of collaborating with HR to integrate data-driven culture into employee onboarding and development programs. By making data literacy and AI skills a core part of employee training, organizations can ensure that their workforce is well-equipped to leverage these tools effectively. Mercado Livre’s partnership with HR helped them to scale their data culture efforts and make it a fundamental part of their employees’ growth and development.
Finally, Gonçalves emphasized the importance of continuously measuring and iterating on data-driven initiatives. By tracking key metrics such as the Data Driven Index and regularly seeking feedback from employees, organizations can identify areas for improvement and make data-informed decisions to optimize their strategies. This iterative approach ensures that data and AI initiatives remain aligned with business objectives and drive meaningful impact.
As organizations navigate the challenges and opportunities of the AI era, Mercado Livre’s experience serves as a valuable case study in democratizing data and AI while fostering a data-driven culture. By empowering employees at all levels to leverage these tools and cultivating a mindset that embraces data-driven decision-making, companies can position themselves for success in our AI-driven world.
