Lalit Ahuja

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Lalit Ahuja
Position:
Chief Technology Officer
Bio:

Lalit Ahuja is responsible for ensuring customers gain the most value from their GridGain investments. He oversees delivery of vertically-aligned solutions in collaboration with GridGain’s strategic partners and leads a global team of solution architects focused on customer success.

In his career spanning over 20 years, Lalit has led various IT functions including enterprise architecture, product management, large scale program management, IT operations and served as a digital strategy advisor to executives at Fortune 500 enterprises.

Prior to GridGain, Lalit led the global Customer Success team at Akana, a leader in API Management and Application Services Governance space, where he was responsible for increased customer retention and more than 300% growth in Akana’s consulting services business.

Lalit holds a Master’s degree in Engineering and an MBA from UCLA.

Bio:

Lalit Ahuja is responsible for ensuring customers gain the most value from their GridGain investments. He oversees delivery of vertically-aligned solutions in collaboration with GridGain’s strategic partners and leads a global team of solution architects focused on customer success.

In his career spanning over 20 years, Lalit has led various IT functions including enterprise architecture, product management, large scale program management, IT operations and served as a digital strategy advisor to executives at Fortune 500 enterprises.

Prior to GridGain, Lalit led the global Customer Success team at Akana, a leader in API Management and Application Services Governance space, where he was responsible for increased customer retention and more than 300% growth in Akana’s consulting services business.

Lalit holds a Master’s degree in Engineering and an MBA from UCLA.

In a previous article, I discussed redefining the challenge facing companies that want to become data-driven. The way most people think about this problem – and the most commonly proposed solution – is putting all data into a single place, such as a data lake. This strategy has challenges, the biggest of which is that while data lakes make it economical to store data, retrieval, and analysis…