Unravel Data: Facilitating Advanced DataOps for Efficient Cloud Migrations

KunalAgarwal, Co-founder and CEO
According to Statista, the digital world will generate 97 zettabytes of data in 2022 alone, which is predicted to grow and reach 181 zettabytes by 2025. The desire to capitalize on the accelerating growth of data is evident from the skyrocketing adoption of cloud infrastructure within global enterprises. However, migrating data-driven applications to the cloud can be complicated and costly without a complete picture of the data sources, systems, and dependencies required for effective business operations.

Unravel Data comes in as a game changer to support businesses in efficiently navigating through the everevolving cloud arena with its DataOps observability platform. DataOps observability ensures a client’s data applications generate quick, reliable, and cost-efficient analytics capable of empowering impactful outcomes across banking, insurance, healthcare, retail, and hi-tech industries. Modern data applications power innovative and soughtafter capabilities like fraud detection, personalization, and customer 360. Unravel’s DataOps observability platform extracts meaningful insights into what’s going on across the complex modern data stack, pinpoints problems and inefficiencies, and delivers prescriptive AI-enabled recommendations on how to make things better.

The Unravel DataOps observability platform harnesses full-stack visibility, contextual awareness, AI-powered intelligence, and automation to help data teams migrate data applications to the cloud on time and on budget while consistently fulfilling internal and external service-level agreements (SLAs). Essentially, Unravel provides end-toend visibility and AI-powered guidance to help enterprises moving to the cloud understand and optimize the performance and cost of their data-driven applications.

“We help our clients make data-driven decisions at every step of their cloud migration, from discovery to assessment to then actually migrating to the cloud and scaling and optimizing workloads once there, “ says Kunal Agarwal, cofounder and CEO of Unravel Data.

Specializing in big data applications and pipelines, Unravel mitigates evolving cloud migration challenges. Through its AI, the company provides in-depth insights that boost a client’s ability to pre-determine the costs of a cloud migration project, enabling a final implementation strategy that delivers exceptional system performance and reliability.

The DataOps observability platform comprehensively discovers everything that’s running in onpremises data centers to analyze existing workloads, datasets, applications, users, and processing engines to understand storage and infrastructure requirements, dependencies, compatibilities, as well as and SLAs.

Unravel correlates the information on applications, users, datasets, and computing resources to connect the dots for all workloads. It shows exactly how specific workloads would map to the cloud—including projected costs— and runs “what if” scenarios to evaluate different options.
Once workloads are on the cloud, Unravel uses autobaselining, anomaly detection, and other data science algorithms to identify cost efficiencies and performance improvements. The birth of Unravel’s DataOps observability for cloud migration and management stemmed from the seismic shift of companies moving to today’s modern data stack.

Without automated full-stack discovery and contextual correlation, a deep understanding of workload requirements and dependencies, and AI optimization, it was taking companies months of manual effort to assess their data ecosystem (and they would still wind up with blind spots) then make best-guess planning decisions. Often, migrations were running over budget and behind schedule. Unravel enables quick and well-strategized data-driven migrations where a firm’s data application requirements, pipeline dependencies, and users are profiled to estimate and regulate the budget and timeline of the data workload migration.

We help our clients make data-driven decisions at every step of their cloud migration, from discovery to assessment to then actually migrating to the cloud and scaling and optimizing workloads once there

Having partnered with numerous top cloud providers, including Amazon Web Services (AWS), Microsoft Azure, and Google Cloud, Unravel has a good percentage of Fortune 500 clients across various industries. One is the software giant Adobe, which approached Unravel for additional information and insights about its data workloads. Unravel helped them migrate their onpremises data onto the cloud without disruptions. It began with the discovery and assessment of Adobe’s entire data ecosystem, eliminating months of lengthy, iterative trial-and-error exercises. Subsequently, Unravel provided complete visibility across Adobe’s ecosystem, conducted a whatif analysis for the correct sequencing of migrating their applications, accurately forecasted cloud cost improvements, and assessed computer resource requirements with tradeoff analyses. For example, by deploying an on-premises workload in an auto-scaling environment, Unravel projected Adobe could save more than 57% of the cost. To rectify inefficiencies, errors, and reliability issues, Adobe’s sales, marketing, and product data pipelines were analyzed, ensuring precise fulfillment of SLA specifications.

The rising significance of customercentricity and changing cloud migration perceptions are driving Unravel’s growth. Moving forward, it aims to continually improve its products to help clients evolve and transform their existing IT posture into a highly efficient cloud infrastructure .

Unravel Data

Palo Alto, CA

KunalAgarwal, Co-founder and CEO

Unravel’s DataOps observability platform enables your data teams to intelligently optimize, automatically troubleshoot and proactively control costs and quality of data pipelines and applications. Designed for modern data stacks, Unravel captures, correlates, and analyzes the granular insights you need to maximize business value from data.

Unravel Data