Palo Alto, CA, USA
Mar 6, 2023 | By Stephen Lamont
Most organizations spend at least 37% (sometimes over 50%) more than they need to on their cloud data workloads. A lot of costs are incurred down at the individual job level, and this is usually where there’s the biggest chunk of overspending. Two of the biggest culprits are oversized resources and inefficient code. But for an organization running 10,000s or 100,000s of jobs, finding and fixing bad code or right-sizing resources is shoveling sand against the tide.
Feb 24, 2023 | By Jason English
IT and data executives find themselves in a quandary about deciding how to wrangle an exponentially increasing volume of data to support their business requirements – without breaking an increasingly finite IT budget. Like an overeager diner at a buffet who’s already loaded their plate with the cheap carbs of potatoes and noodles before they reach the protein-packed entrees, they need to survey all of the data options on the menu before formulating their plans for this trip.
Feb 22, 2023 | By Jason Bloomberg
By Jason Bloomberg, President, Intellyx Part 2 of the Demystifying Data Observability Series for Unravel Data In part one of this series, fellow Intellyx analyst Jason English explained the differences between DevOps and DataOps, drilling down into the importance of DataOps observability. The question he left open for this article: how did we get here? How did DevOps evolve to what it is today, and what parallels or differences can we find in the growth of DataOps?
Feb 13, 2023 | By Jason English
DevOps was started more than a decade ago as a movement, not a product or solution category. DevOps offered us a way of collaborating between development and operations teams, using automation and optimization practices to continually accelerate the release of code, measure everything, lower costs, and improve the quality of application delivery to meet customer needs.
Feb 9, 2023 | By Unravel Data
As organizations run more data applications and pipelines in the cloud, they look for ways to avoid the hidden costs of cloud adoption and migration. Teams seek to maximize business results through cost visibility, forecast accuracy, and financial predictability. Watch the breakout session video from Data Teams Summit and see how organizations apply agile and lean principles using the FinOps framework to boost efficiency, productivity, and innovation. Transcript available below.
Feb 9, 2023 | By Unravel Data
As DataOps moves along the maturity curve, many organizations are deciphering how to best balance the success of running critical jobs with optimized time and cost governance. Watch the fireside chat from Data Teams Summit where Mark Sear, Head of Data Platform Optimization for Maersk, shares how his team is driving towards enabling strong engineering practices, design tenets, and culture at one of the largest shipping and logistics companies in the world.
Feb 3, 2023 | By Stephen Lamont
Uncontrolled cloud costs pose an enormous risk for any organization. The longer these costs go ungoverned, the greater your risk. Volatile, unforeseen expenses eat into profits. Budgets become unstable. Waste and inefficiency go unchecked. Making strategic decisions becomes difficult, if not impossible. Uncertainty reigns.
Jan 24, 2023 | By Unravel Data
This Eckerson Group report gives you a good understanding of how the Unravel platform addresses multiple categories of data observability—application/pipeline performance, cluster/platform performance, data quality, and, most significant, FinOps cost governance—with automation and AI-driven recommendations.
Jan 6, 2023 | By Stephen Lamont
Data teams and their business-side colleagues now expect—and need—more from their observability solutions than ever before. Modern data stacks create new challenges for performance, reliability, data quality, and, increasingly, cost. And the challenges faced by operations engineers are going to be different from those for data analysts, which are different from those people on the business side care about. That’s where DataOps observability comes in.
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.
Mar 2, 2023 | By Unravel
Collaborate across your data team to optimize performance, control costs, and improve quality Join SanjMo Advisory Services Founder Sanjeev Mohan and Unravel Data VP of Solutions Engineering Chris Santiago to learn how organizations are applying FinOps best practices to improve efficiency for the modern data stack. Data management services are the fastest-growing category of cloud service spending, representing approximately 40% of the total cloud bill. 80% of data management professionals report difficulty accurately forecasting data-related cloud costs.
Dec 21, 2022 | By Unravel
Data teams like yours face new challenges as they manage an increasing variety of data formats, expanding use cases, and as data volumes double every three years. Organizations increasingly depend on new data products to meet their financial objectives. Join SanjMo Advisory Services Co-Founder Sanjeev Mohan and Unravel Data Vice President of Solutions Engineering Chris Santiago to learn.
Dec 20, 2022 | By Unravel
What's new and a look a head: Unlocking Value with Unravel presented by VP of Solutions Engineering Chris Santiago.
Dec 8, 2022 | By Unravel
Data management is fundamental to every application. Managing this precious asset is an essential competency in modern businesses of every sort. Innovations in data platforms are being adopted, and data management approaches are evolving rapidly to keep pace. Increasingly, enterprises are converging their data warehouse, data lake, and other data management platforms onto distributed cloud-native infrastructures. As more types of data are consolidated into their platforms, enterprises implement more scalable DataOps pipelines and more comprehensive governance practices to manage it all.
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.
Jan 13, 2020 | By Unravel
Learn more about AI-powered data operations for modern data applications.
Jan 13, 2020 | By Unravel
Learn how to simplify Big Data Operations with Application Performance Management.
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.
Get the visibility you need at each stage of your machine learning application development lifecyle.
Learn how to ensure that streaming data analytics perform reliably.
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.
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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.