Microsoft’s VP of Data & AI chairs as Unravel Data’s Board of Directors

Unravel Data has announced the appointment of Zia Mansoor to the company’s Board of Directors. Mansoor currently serves as Microsoft’s Vice President of Data & AI, and has extensive expertise in go-to-market strategy and providing product and solution leadership across operational database, analytics, AI/Machine Learning, data governance, and business intelligence solutions. 

“We are excited to welcome Zia to our Board. He’s had tremendous success enabling customers to build efficient and scalable solutions while instilling a strong data culture within organizations. His appointment reflects our strong relationship with M12, Microsoft’s venture fund, a key investor in Unravel. We look forward to working together as Unravel continues to help organizations efficiently deliver data outcomes and effectively control skyrocketing cloud compute and storage costs”, said Kunal Agarwal, CEO of Unravel Data.

Mansoor has held various positions at Microsoft for the last 15 years. Prior to his current role leading Worldwide Data and AI commercial business, he led Microsoft Canada’s largest team of technical professionals as Vice President of Customer Success. Mansoor has helped numerous organizations accelerate their journey to the cloud and realize potential across all Microsoft commercial solution areas, including Modern Workplace, Azure (App Development and Infrastructure, Data and AI), Business Applications, and Security. 

According to Mansoor, “I am excited to work with Unravel Data, which has proven itself to be a fast-growing data observability company. Alongside my fellow advisors, I look forward to helping drive innovation in its data operations solutions. I have long admired the team, their work, and how they are leveraging AI to meet the growing opportunities for the modern data stack.”

Founded by data pioneers Kunal Agarwal and Dr. Shivnath Babu, Unravel Data understands that the exponential growth of data combined with the broad adoption of the public cloud requires an entirely new way to manage and optimize the data pipelines that support the real-time analytics needs of today’s data-driven enterprises.