#data democratization

[newfangled-vady]

Top 5 Benefits of Low-Code/No-Code BI Solutions

Low-code/no-code Business Intelligence (BI) solutions offer a paradigm shift in analytics, providing organizations with five key benefits. Firstly, rapid development and deployment empower businesses to swiftly adapt to changing needs. Secondly, these solutions enhance collaboration by enabling non-technical users to contribute to BI processes. Thirdly, cost-effectiveness arises from reduced reliance on IT resources and streamlined development cycles. Fourthly, accessibility improves as these platforms democratize data insights, making BI available to a broader audience. Lastly, agility is heightened, allowing organizations to respond promptly to market dynamics. Low-code/no-code BI solutions thus deliver efficiency, collaboration, cost savings, accessibility, and agility in the analytics landscape.

[techinfotrends]

Discover how democratizing data can bridge the talent gap in your organization. Gain insights into the strategies and tools needed to make data accessible to all, and unlock the potential for thriving business growth.

[rajaniesh]

From Data to Decisions: Empowering Teams with Databricks AI/BI

🚀 Unlock the Power of Data with Databricks AI/BI! 🚀 Imagine a world where your entire team can access data insights in real-time, without needing to be data experts. Databricks AI/BI is making this possible with powerful features like conversational AI

In today’s business world, data is abundant—coming from sources like customer interactions, sales metrics, and supply chain information. Yet many organizations still struggle to transform this data into actionable insights. Teams often face siloed systems, complex analytics processes, and delays that hinder timely, data-driven decisions. Databricks AI/BI was designed with these challenges in…

[procurement-insights]

What is your least favorite ProcureTech BUZZword or term?

Here is one of my least favorite ProcureTech terms or buzzwords - what's your?

What is democratizing data? Data democratization is the ongoing process of enabling everybody in an organization, irrespective of their technical know-how, to work with data comfortably, to feel confident talking about it, and, as a result, to make data-informed decisions and build customer experiences powered by data. – Amplitude, Jan 27, 2022 What is the democratization of AI data? AI…

[gleecus-techlabs-blogs]

Data democratization helps companies make data-driven decisions by creating systems and adopting tools that allow anyone in the organization, regardless of their technical background, to access, use and talk about the data they need with ease.

[elsa16744]

Exploring the Latest Data Analytics Trends | SG Analytics

The data analytics industry has evolved, delivering new solutions to business problems. This post discusses the latest data analytics trends.

[alwaysbewoke]

here is the sheet. it's an excel spreadsheet so it will download to your computer. this is really important for all the people who constantly say "democrats and republicans are the same." if they're not willing to do the work to either prove or disprove that notion, they're NOT someone ANYONE should be taking political advice from.

[my-midlife-crisis]

EAT THE RICH

[immortalsins]

uni results come out at 2pm today and my mother has decided it's the perfect day to head up a mountain

[newfangled-vady]

VADY is more than just an analytics platform—it’s an AI-powered intelligence engine that understands business context. By combining context-aware AI analytics with advanced reasoning, VADY delivers insights that drive real business impact. Businesses no longer need to sift through endless reports—VADY’s conversational analytics platform provides real-time, actionable intelligence that fuels growth and success. Make better business decisions today with VADY!

[qqueenofhades]

Going to cautiously posit that if they're moving toward calling Kentucky for Beshear (incumbent Democratic governor) in a blindingly red state Trump won by 30 points, in an off-year election, about 30 minutes after polls close statewide, that is a Good Sign.

[relaxedstyles]

[procurement-insights]

An important exchange on AI with Google's AI champion

A timely GenAI exchange with Google AI Champion

[more-flotsam-and-jetsam]

[jcmarchi]

Gartner Data & Analytics Summit São Paulo: Mercado Livre’s AI and Data Democratization in Brazil

New Post has been published on https://thedigitalinsider.com/gartner-data-analytics-summit-sao-paulo-mercado-livres-ai-and-data-democratization-in-brazil/

Gartner Data & Analytics Summit São Paulo: Mercado Livre’s AI and Data Democratization in Brazil

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.