Harnessing Data, AI, and Cloud to Transform Decision Making

Corporate data and analytics strategies have undergone a significant transformation in the past year. These sectors have shifted their focus from internal process optimization and AI-driven decision-making to ethical and responsible data utilization, strict regulatory adherence, and data protection. This evolution also includes the deep integration of AI into products and services, as well as data democratization, says Ernesto Serrano, General Manager, Snowflake Mexico.

"AI is becoming fundamental, making the ethical and responsible use of data crucial. Generative AI is not the objective itself, but a transformative element for people and companies to impact business processes. The focus should not be on Generative AI as the destination, but rather as the path,” says Serrano.

Serrano highlights that the industry is moving towards an AI-centric future built on a foundation of data, with AI being deeply integrated into products and services to generate tangible business value. He emphasizes the transformative potential of Generative AI across various organizational domains through the strategic application of data.  

Snowflake, says Serrano, identified two key technological disruptions significantly influencing data and analytics strategies. The first is ensuring data interoperability, requiring companies to construct flexible architectures capable of integrating diverse data sources through open table formats, open catalogs for data access management, and optimal processing engines for specific use cases.

The second is AI, particularly Generative AI, which is having a profound impact. Serrano underscores that about 80% of global data is now unstructured. To use it effectively for informed decision making, businesses need to converge structured and unstructured data in analytical processes across all channels. "Technological disruptions are a constant. The key is to understand that technological disruption is not a problem, but an opportunity, and organizations that can anticipate these disruptions will be best positioned,” Serrano says.

Snowflake is enabling organizations to leverage these disruptions. The company’s solutions unify data and AI capabilities within a robust ecosystem, says Serrano. He adds that these solutions are easy to use, connected, and reliable. They can also adapt to evolving data architectures and democratize data access for users with varying technical expertise, from SQL and Python proficiency to natural language queries, all while ensuring stringent security and governance.

Snowflake’s ecosystem has grown rapidly over the past five years. The platform supports over 11,000 customers who collectively run more than 6.4 billion queries daily, says Serrano. The ecosystem includes thousands of companies, with over 680 actively sharing more than 2,500 datasets and applications on the Snowflake Marketplace. "We offer a marketplace where customers can commercialize their data, generating 115,000 monthly visits; it is a space to create a strong income source for their companies,” says Serrano. 

The more data companies use, the better decisions they can make, says Serrano. For that reason, he urges companies to use more than their own internal data, but to also incorporate the data generated by their customers, suppliers, and their suppliers’ suppliers.

For example, says Serrano, Nissan uses Snowflake to analyze customer reviews and posts from various online forums. This enables the company to gain valuable insights into customer experiences at dealerships, ultimately improving overall customer satisfaction. By leveraging Snowflake, Nissan reportedly achieved results two months faster than with other technological alternatives, processed millions of records in seconds, and attained a 97% effectiveness rate in sentiment analysis, directly impacting its customer experience strategies.

Companies such as WHOOP and Travelpass achieved a 65% cost reduction and a 350% increase in data delivery speed by using Snowflake, says Serrano. Blue Yonder also successfully leveraged the technology to optimize its processes, he adds.

However, data democratization is an essential step, as data should not be confined to specific teams within an organization but made accessible to all relevant actors, says Serrano. He highlights that Snowflake actively promotes data democratization within organizations and their ecosystems, empowering individuals with varying levels of technical expertise to leverage data for insights and decision-making.