The rapid pace at which AI-related technologies have been embraced by enterprises means that companies are not sitting on the sidelines, waiting to see what the competition comes up with. Yet, as companies aim to utilize AI and large language models for innovation, they face the daunting challenges of massive data needs, lack of visibility into performance issues, and scarce expertise to mitigate problems. Moreover, most remain in the dark about their costs.

On your podcast, Kunal will delve into the intricacies of AI costs and the significance of data observability for speed, scale, and cloud data cost management. referencing cost models defined by a recent McKinsey study, he will shed light on the cost levers of AI innovation on the cloud, show why having deep visibility helps data teams optimize data workloads and data pipelines for speed and cost efficiency, and illustrate how data observability and FinOps with AI purpose-built for specific cloud data platforms can help automate the process. Kunal will also emphasize the cultural Shift-Left transformation data teams need to make to hold individuals accountable for their cloud data usage and costs.

With the surge in cloud adoption, managing costs is challenging. Data is the fastest growing expense of cloud computing costs – representing 39% of the total cloud bill and rising. Many organizations grapple with having visibility into their real-time cloud data utilization, and understanding and managing the levers that lead to unexpected high bills. The complexity of cloud data platforms, combined with the sheer amount of workloads running in production, and lack of visibility into job and user level visibility makes cloud data cost management daunting, with most tools offering a limited view of only infrastructure costs.

On your podcast, Kunal will unpack the intricacies of cloud expenses, sharing insights into the true drivers behind these costs. Through automation and AI, Kunal believes that companies can achieve a more granular understanding of their cloud data costs. He’ll also delve into the growing importance of the FinOps practice, highlighting how it can be a game-changer in ensuring a more transparent and efficient cloud data strategy for businesses.