Companies are under pressure to deliver faster innovation, enabled by cloud-based data analytics and AI. In order to deliver faster business value, data teams are looking to achieve speed and scale through data and AI pipeline performance and efficiency. A recent MIT Technology Review Insights report finds that 72% of technology leaders agree that data challenges are the most likely factor to jeopardize AI/ML goals.
Explosion of data volume. Source: Statistica
Leverage the power of both data lakes and data warehouses
The Databricks Lakehouse Platform seamlessly combines structured, semi-structured, and unstructured data in one place, enabling businesses to harness the power of both data lakes and data warehouses with a single architecture. This means that enterprises no longer have to manage multiple systems or struggle with different formats. Whether it’s relational databases or raw log files, a lakehouse enables you to easily ingest and process all types of data for ELT/ETL, streaming data pipelines, BI dashboards, data science and ML model serving.
The need for expertise
As data volumes expand, businesses need to rapidly scale their lakehouse estates without overburdening their data teams. To unlock the full potential of the lakehouse, organizations need experts who can architect, build, deploy, and operate data and AI pipelines on the lakehouse. Data teams increasingly look to data observability to augment their expertise at every phase of the data life cycle. Scaling expertise ensures that businesses achieve optimal performance as they process vast and growing amounts of data.
Databricks Lakehouse monitoring, observability, and FinOps
Monitoring, observing, and managing your Databricks Lakehouse environment helps ensure smooth operation. Databricks Lakehouse Monitoring helps ensure that your data and AI assets are high quality, accurate, and reliable through deep insight into the lineage of your data and AI assets. Unravel leverages a wide variety of inputs—including usage analytics and billing information from Unity Catalog system tables—to enable full-spectrum data observability and FinOps for your lakehouse.
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Unravel’s purpose-built AI for Databricks
Unravel’s purpose-built AI for Databricks delivers insights based on Unravel’s deep observability at the job, user, and code level to provide AI-driven performance and cost efficiency recommendations, including compute provisioning, query performance, autoscaling efficiencies, and more.
Unlike generic AI tools, Unravel’s AI-powered Insights Engine is purpose-built for Databricks and other modern data platforms. Unravel goes deep to enable data observability and FinOps for your lakehouse at the scale you need to overcome challenges in the ML lifecycle and achieve your business goals with data.
Unravel for Databricks enables organizations to speed cloud transformation initiatives by having real-time cost visibility, predictive spend forecasting, and performance insights for their workloads. Accelerate time to value for your new AI initiatives by mitigating potential pipeline bottlenecks and associated costs before they occur. Manage and optimize the ROI of your data projects with customized dashboards and alerts that offer insights on spend, performance, and unit costs.
Unravel delivers AI-powered insights to get more workloads into your lakehouse, faster
Gain visibility into system performance and efficiency
Using out-of-the-box dashboards and reports, Unravel helps you immediately deliver faster performance to run 50% more workloads on the lakehouse, launch new applications 3x faster, achieve ±10% accuracy for your lakehouse budget forecasts, and achieve 99%+ SLAs. With Unrave’s data observability and FinOps for Databricks, you can keep a close eye on the overall performance of your data lakehouse. Unravel enables you to manage and govern performance and efficiency to help you deliver faster results and achieve profitability goals.
Proactively identify and address issues in real time
With Unravel for Databricks, you can proactively identify and resolve issues with real-time visibility, AI-powered recommendations, and automated guardrails. Whether it’s a sudden spike in resource consumption or a long-running query, Unravel can help you proactively address issues before they ever make it to production. By addressing performance and efficiency early in the process, you can minimize downtime and ensure uninterrupted productivity.
DevOps CI/CD integration
Unravel integrates with popular DevOps tools like GitHub and Azure DevOps. This provides actionability in CI/CD workflows by enabling early issue detection during the code-merge phase and providing developers real-time insights into the potential financial impact of their code changes. This results in fewer production issues and improved cost efficiency.
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Partnering to deliver data observability for the lakehouse
Databricks and Unravel are teaming up to enhance data observability and FinOps for the lakehouse. Partnering with trusted companies in the industry allows Databricks to leverage their expertise and combine it with its own knowledge and technology. This collaboration ensures that customers can benefit from the best of both worlds, optimizing the performance and observability of their Lakehouse deployments.
Having access to specialized tools is crucial. Through this partnership, Databricks customers have access to an integrated solution, specifically designed for the lakehouse. Unravel enables you to get deep insights into the performance and usage of your data pipelines, workflows, and analytics workloads.
Unlock your lakehouse potential with Databricks and Unravel
By harnessing the power of Databricks’ Lakehouse Platform and Unravel’s purpose-built AI, you can achieve your data and AI goals with enhanced observability, optimized performance, and unparalleled efficiency. Get started with Databricks and Unravel today to make the most of your Databricks Lakehouse Platform investment. Learn more about Unravel for Databricks and Create your free account.
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