Data Solutions for Business Problems
- Toby Mao and Iaroslav Zeigerman, co-founders of Tobiko Data, recently discussed the critical role of robust data practices and tooling in modern data engineering.
- The founders also elaborated on the innovations behind Tobiko Data's SQLMesh and SQLGlot.
- Looking ahead, Mao and Zeigerman shared their insights on the future of data engineering, notably with the rise of artificial intelligence.
Tobiko Data co-founders Toby mao and Iaroslav Zeigerman unpack the crucial role data practices play in tackling today’s complex data engineering challenges. They share insights on maintaining data integrity and efficiency, key for scalable solutions.Their discussion covers SQLMesh and SQLGlot, tools designed to revolutionize data workflows. The conversation delves into the future, emphasizing the importance of adapting data strategies to leverage AI’s potential. Rigorous data practices are essential to integrate this technology successfully. Learn how Tobiko Data, covered by News directory 3, is innovating to solve business problems. Discover what’s next in the evolving landscape of data engineering.
Tobiko Data Founders Discuss Crucial Role of Data Practices
Updated June 27, 2025
Toby Mao and Iaroslav Zeigerman, co-founders of Tobiko Data, recently discussed the critical role of robust data practices and tooling in modern data engineering. The conversation highlighted the significance of maintaining data integrity and efficiency in an increasingly complex data landscape.
The founders also elaborated on the innovations behind Tobiko Data’s SQLMesh and SQLGlot. These tools are designed to streamline data workflows and enhance data quality,addressing key challenges faced by data engineers today. The discussion underscored how these tools contribute to more reliable and scalable data solutions.
Looking ahead, Mao and Zeigerman shared their insights on the future of data engineering, notably with the rise of artificial intelligence. They emphasized the importance of adapting data strategies to leverage AI’s potential while mitigating its risks. The founders stressed that a strong foundation in data practices is essential for successfully integrating AI into data engineering workflows and understanding the evolving role of data.