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Logistics giant optimizes cloud data costs up front at speed & scale

One of the world’s largest logistics companies leverages automation and AI to empower every individual data engineer with self-service capability to optimize their jobs for performance and cost. The company was able to cut its cloud data costs by 70% in six months—and keep them down with automated 360° cost visibility, prescriptive guidance, and guardrails for its 3,000 data engineers across the globe.

The Modern Data Ecosystem: Choose the Right Instance

There are several ways to optimize cloud storage, depending on your specific needs and circumstances. Here are some general tips that can help: Overall, optimizing cloud storage requires careful planning, monitoring, and management. By following these tips, you can reduce your storage costs, improve your data management, and get the most out of your cloud storage investment.

Build vs. Buy: 5 Q's to Guide Data Observability

How data teams get the most value from open source and commercial tools Join Hilman Associates Cloud Finance Manager Eric Hilman, DBGurus FinOps Certified Practitioner Joe Ferrero, and Unravel Data Senior Solutions Engineer Don Hilborn as we discuss considerations organizations face when choosing whether to build solutions based on open source software (OSS) or purchase commercial off-the-shelf (COTS) software.

DBS Discusses Data+FinOps for Banking

DBS Bank Head of Automation, Infrastructure for DBS Big Data, AI and Analytics Luis Carlos Cruz Huertas has a 1-on-1 discussion with Unravel CEO and Co-founder Kunal Agarwal about the convergence of DataOps and FinOps. The discussion, Leading Cultural Change for Data Efficiency, Agility, and Cost Optimization, was held at a recent Untap event in New York and revolves around best practices, lessons learned, and insights on.

DataOps Resiliency: Tracking Down Toxic Workloads

In the first three articles in this four-post series, my colleague Jason English and I explored DataOps observability, the connection between DevOps and DataOps, and data-centric FinOps best practices. In this concluding article in the series, I’ll explore DataOps resiliency – not simply how to prevent data-related problems, but also how to recover from them quickly, ideally without impacting the business and its customers.

Getting Started: FinOps for Your Modern Data Stack

Increase data pipeline reliability and efficiency to achieve business impact Data is a key enabler of digital transformation, yet organizations struggle to manage cloud data costs. FinOps is a cultural shift that integrates financial accountability into cloud operations. Join FinOps Foundation Director of Cost Optimization Lindbergh Matillano and Unravel Data Director of Product Marketing Clinton Ford to improve the cost efficiency of your modern data stack using FinOps best practices.

Solving key challenges in the ML lifecycle with Unravel and Databricks Model Serving

Machine learning (ML) enables organizations to extract more value from their data than ever before. Companies who successfully deploy ML models into production are able to leverage that data value at a faster pace than ever before. But deploying ML models requires a number of key steps, each fraught with challenges.