Unravel

Palo Alto, CA, USA
2013
Oct 7, 2022   |  By Unravel Data
Unravel now pulls in data quality checks from external tools into its single-pane-of-glass full-stack observability view.
Oct 5, 2022   |  By Stephen Lamont
DBTA recently hosted a roundtable webinar with four industry experts on “Unlocking the Value of Cloud Data and Analytics.” Moderated by Stephen Faig, Research Director, Unisphere Research and DBTA, the webinar featured presentations from Progress, Ahana, Reltio, and Unravel. You can see the full 1-hour webinar “Unlocking the Value of Cloud Data and Analytics” below. Here’s a quick recap of what each presentation covered.
Oct 5, 2022   |  By Kunal Agarwal
I was chatting with Sanjeev Mohan, Principal and Founder of SanjMo Consulting and former Research Vice President at Gartner, about how the emergence of DataOps is changing people’s idea of what “data observability” means. Not in any semantic sense or a definitional war of words, but in terms of what data teams need to stay on top of an increasingly complex modern data stack.
Sep 28, 2022   |  By Steve Lamont
Chief Data & Analytics Officer UK (CDAO UK) is the United Kingdom’s premier event for senior data and analytics executives. The three-day event, with more than 200 attendees and 50+ industry-leading speakers, was packed with case studies, thought leadership, and practical advice around data culture, data quality and governance, building a data workforce, data strategy, metadata management, AI/MLOps, self-service strategies, and more.
Sep 19, 2022   |  By Unravel Data
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.
Sep 15, 2022   |  By Unravel Data
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.
Sep 1, 2022   |  By Stephen Lamont
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.
Aug 30, 2022   |  By Stephen Lamont
The Eckerson Group recently presented a CDO TechVent that explored data observability, “Data Observability: Managing Data Quality and Pipelines for the Cloud Era.” Hosted by Wayne Eckerson, president of Eckerson Group, Dr.
Aug 23, 2022   |  By Chris Meyer
Summary: Sometimes the insight you’re shown isn’t the one you were expecting. Unravel DataOps observability provides the right, and actionable, insights to unlock the full value and potential of your Spark application. One of the key features of Unravel is our automated insights. This is the feature where Unravel analyzes the finished Spark job and then presents its findings to the user. Sometimes those findings can be layered and not exactly what you expect.
Jul 18, 2022   |  By Chris Santiago
Apache Kafka is an open-source distributed event streaming platform used by thousands of companies for high-performance data pipelines, streaming analytics, data integration, and mission-critical applications. Administrators, developers, and data engineers who use Kafka clusters struggle to understand what is happening in their Kafka implementations.
Nov 1, 2022   |  By Unravel
As organizations seek to become more competitive, they are often looking to enrich their data sets for analytics to gain deeper insights. The data used for enrichment may include text data, machine data, image data, geospatial data, and real-time data. This data may be high volume, highly diverse, and disparate in nature. As part of this effort, organizations are moving to cloud data platforms to store and manage this modern data.
Nov 1, 2022   |  By Unravel
Designed to be fast, scalable, flexible, and user-friendly, modern applications are at the center of the innovation and automation that is transforming companies, industries, and society today. At the same time, modern applications, increasingly built with microservices, also come with requirements that traditional data management approaches fall far short of effectively meeting.
Oct 27, 2022   |  By Unravel
Data teams need to be able to set cloud data budgets at a specific scope - and know if your various teams or departments are tracking to those budgets. But today, most data teams only know that the budget was overrun after it’s too late. With Unravel, establishing and tracking budgets to prevent overruns is easy.
Oct 20, 2022   |  By Unravel
Bringing Your Data Cloud Bill Under Control presented by Keith Alsheimer, CMO, Unravel Data at CDAO Fall 2022. During this presentation, Keith shares how the Unravel Data DataOps observability platform helps data teams.
Oct 4, 2022   |  By Unravel
From data lakes and data warehouses to data mesh and data fabric architectures, the world of analytics continues to evolve to meet the demand for fast, easy, wide-ranging data insights. Right now, nearly 50% of DBTA subscribers are using public cloud services, and many are investing further in staff, skills, and solutions to address key technical challenges. Even today, the amount of time and resources most organizations spend analyzing data pales in comparison to the effort expended in identifying, cleansing, rationalizing, consolidating, and transforming that data.
Sep 28, 2022   |  By Unravel
We have closed a $50 million Series D round of funding, led by Third Point Ventures with participation from Bridge Bank and existing investors that include Menlo Ventures, Point72 Ventures, GCV Capital, and Harmony Capital. Kunal Agarwal, CEO and Co-Founder, shares what this funding means for you.
Sep 27, 2022   |  By Unravel
Unravel is a DataOps observability platform that enables your data teams to optimize the cost of your data operations intelligently, run faster data pipelines, and troubleshoot mission-critical applications. Watch this video to discover what’s new in Unravel Data 4.7.5.0 release.
Sep 26, 2022   |  By Unravel
For DataOps teams, job failures are common. But finding the issue is (traditionally) where things get even worse. It can take hours or days to troubleshoot a job failure. Unravel Data provides a single view where DataOps teams can locate exactly where–and why–a job failed, along with precise recommendations to troubleshoot the error. DataOps teams are now able to both diagnose and troubleshoot job failures in minutes instead of days or weeks.
Sep 26, 2022   |  By Unravel
Data pipelines fail all the time for a variety of reasons; service downtime, data volume fluctuations, etc. Diagnosing these failures manually is very difficult and time consuming. Unravel Data allows DataOps teams to troubleshoot pipeline failures automatically – showing exactly where and why a pipeline failed, and precise recommendations to remedy the issues. Using Unravel, DataOps teams can now diagnose and fix data pipeline failures in a fraction of the time.
Sep 26, 2022   |  By Unravel
To ensure that jobs are running optimally, DataOps teams need to look at the detailed code. But DataOps teams don’t have the right tools to easily examine problematic code - or a simple path to optimizing it. With Unravel Data, DataOps teams can quickly troubleshoot applications that are throwing errors - all the way down to a specific line of problematic code. All in a single view.
Jan 13, 2020   |  By Unravel
Learn how to simplify Big Data Operations with Application Performance Management.
Jan 13, 2020   |  By Unravel
Learn more about AI-powered data operations for modern data applications.
Jan 1, 2020   |  By Unravel
Learn how Unravel complements Cloudera Manager.
Jan 1, 2020   |  By Unravel
Learn a best practice approach to managing performance and utilization.
Dec 1, 2019   |  By Unravel
Get the visibility you need at each stage of your machine learning application development lifecyle.
Dec 1, 2019   |  By Unravel
Learn how to ensure that streaming data analytics perform reliably.
Dec 1, 2019   |  By Unravel
Application Performance Management isn't a new discipline, but it is a new best practice for Big Data. APM for big data has become a must-have for running big data in production in order to manage performance and utilization of big data applications and platforms.

Unravel helps you monitor, manage, and improve your data pipelines in the cloud and on-premises – to drive more reliable performance in the applications that power your business.

The Unravel Data Operations Platform helps ops engineers, app developers, and enterprise architects reduce the complexity of delivering reliable application performance – providing unified visibility and operational intelligence to optimize your entire ecosystem.

Deliver on the promise of data:

  • Uncover: Get a unified view of your entire data stack. Unravel collects performance data from every platform, system, and application on any cloud then uses agentless technologies and machine learning to model your data pipelines from end to end.
  • Understand: Explore, correlate, and analyze everything in your modern data and cloud environment. Unravel’s data model reveals dependencies, issues, and opportunities, how apps and resources are being used, what’s working and what’s not.
  • Unravel: Don’t just monitor performance – quickly troubleshoot and rapidly remediate issues. Leverage AI-powered recommendations to automate performance improvements, lower costs, and prepare for what’s next – wherever it’s deployed.

Simplify Data Operations for Modern Data Clouds.