Systems | Development | Analytics | API | Testing

Demo: Unravel Data - Allocating Costs with Precision Using the Enhanced Chargeback Report

DataOps teams need to understand where costs are going. But the reports provided by cloud vendors aren’t very granular - and they only get the reports after excess costs have been racked up. Unravel allows DataOps teams to understand where costs are going at a detailed level: by user, by service, by department. This information is captured and available as soon as a cluster is detected – allowing DataOps teams to take action and optimize in real time.

Demo: Unravel Data - Automated Budget Tracking to Prevent Overruns

DataOps teams need to be able to set budgets at a specific scope - and know if your various teams or departments are tracking to those budgets. But today, most DataOps teams only know that the budget was overrun after it’s too late. With Unravel, establishing and tracking budgets to prevent overruns is easy.

Demo: Unravel Data - Keep DataOps Budgets On Track (Automatically)

Demo: Unravel Data - Keep DataOps Budgets On Track (Automatically) DataOps teams are paying tremendous amounts of money for cloud instances that were spun up and then forgotten. For larger enterprises, this can equate to millions of dollars in waste. But even for smaller teams, this type of inefficiency is not acceptable. With Unravel, your DataOps team can set a budget/cost threshold (or a time duration), to ensure that you keep your budgets on track. Receive alerts as soon as an instance hits your predefined threshold - instead of discovering it in your monthly bills.

DataOps Observability Designed for Data Teams

Today every company is a data company. And even with all the great new data systems and technologies, it’s people—data teams—who unlock the power of data to drive business value. But today’s data teams are getting bogged down. They’re struggling to keep pace with the increased volume, velocity, variety, complexity—and cost—of the modern data stack. That’s where Unravel DataOps observability comes in.

DataOps Observability: The Missing Link for Data Teams

As organizations invest ever more heavily in modernizing their data stacks, data teams—the people who actually deliver the value of data to the business—are finding it increasingly difficult to manage the performance, cost, and quality of these complex systems. Data teams today find themselves in much the same boat as software teams were 10+ years ago. Software teams have dug themselves out the hole with DevOps best practices and tools—chief among them full-stack observability.

Expert Panel: Challenges with Modern Data Pipelines

Modern data pipelines have become more business-critical than ever. Every company today is a data company, looking to leverage data analytics as a competitive advantage. But the complexity of the modern data stack imposes some significant challenges that are hindering organizations from realizing their goals and realizing the value of data.

A DataOps Observability Dialogue: Empowering DevOps for Data Teams

A DataOps Observability Dialogue: Empowering DevOps for Data Teams It used to be said that software is eating the world, but now data is running things. And it’s high-functioning data teams who make it all happen. But data teams are facing several obstacles that prevent them from delivering innovative analytics at today’s increased speed and scale. Software teams have been facing the same challenges for 10+ years and have tackled them with DevOps. So why are DataOps teams struggling when DevOps teams aren’t? They’re using the same tools to solve basically the same problem. . . .

Unravel Data Demo Video

Unravel’s Keith Alsheimer, Head of Marketing, and Chris Santiago, VP of Solutions Engineering, introduce Unravel’s DataOps observability platform: how it’s designed specifically from the ground up to empower data teams, why DevOps tools don’t work for DataOps, and a short demo of how Unravel AI helps accelerate troubleshooting, automatically where and exactly how to optimize performance, and proactively govern and reduce cloud costs with precision.