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Simplify Data Science and Build Trust in Your Data

Unlock the Full Potential of Your Data with Trel. Experience seamless pipeline automation, advanced data governance, and AI-powered monitoring, enabling your data science team to collaborate efficiently and innovate rapidly.

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Overcoming Data Management Challenges

Data management shouldn’t feel like a relentless puzzle, yet data engineers, scientists and analysts often find themselves trapped in a labyrinth of inefficiency. With current tools, they face a mountain of challenges:

  • Integration Headaches: Integrating different systems often creates a data management nightmare, far from the smooth workflow that was planned.
  • Complex Workflows: Streamlining data pipelines is an everyday challenge, with the tough job of handling dependencies and maintaining data integrity.
  • Quality Quandaries: Ensuring data accuracy across multiple platforms can be like finding a needle in a haystack, consuming precious time and energy.
  • Scalability Stumbles: As data volumes surge, current systems fall behind, struggling to scale and leaving teams always playing catch-up.
  • Experimentation Bottlenecks: Data Scientists face limitations in testing new hypotheses due to slow or cumbersome data pipelines, restricting innovation and creative solutions.
  • Data Discovery Delays: Data Analysts often spend more time searching for the right data rather than analyzing it, delaying insights and slowing down decision-making
  • Collaboration Constraints: Communication breakdowns are inevitable when teams rely on a patchwork of tools, leading to siloed knowledge and disjointed efforts.

Data Engineers spend less than 44% of their time on high value business goals.

What data engineers, data scientists, and data analysts crave is not just incremental improvement but a paradigm shift — a solution where efficiency is embedded in every layer of data management. A world where integration is so seamless, it’s almost invisible, and innovation becomes the day’s main agenda, not an afterthought.

Key Benefits

AI-Assisted Data Observability

Gain instant insights into your data pipeline with natural language queries, powered by advanced AI.

Reproducibility and Auditability

Ensure complete fidelity in recreating experiments, support regulatory compliance with audit trails using immutable data practices and historical data retrieval.

Automated Data Quality Checks

Maintain data integrity with automated quality checks using SodaCore rules, triggering alerts and halting pipelines when necessary.

Self-Healing
Pipelines

Build reliable automation with pipelines that can intelligently recover from delays and failures, ensuring consistent data processing.

Efficient
Data Collaboration

Streamline teamwork through shareable data artifacts and a single source of truth for data identities.

Schema Evolution Management

Easily manage and orchestrate schema migrations with versioning of schema and data quality rules.

Demonstration: Customer Lifetime Value Prediction

See how Trel empowers data scientists to build, manage, and collaborate on a robust CLV prediction pipeline.

Highlights
  • Design and Build: The series covers preparing for data ingestion, principles of formula-based automation, and building Databricks notebooks for CLV features and modeling. It demonstrates how to register, execute, and automate jobs, culminating in a fully automated pipeline.
  • Data Quality Assurance: Watch how Trel and Sodacore implement automated quality checks throughout the CLV model's lifecycle. We demonstrate causing, identifying and fixing data quality issues.
  • Experimentation and Reproducibility: The video covers A/B testing of new features for the CLV model with schema versioning. We show how to deploy new schema and feature code to production, showcasing Trel's streamlined workflows.
  • MLOps Automation: We troubleshoot model validation errors, conduct parameter sweeps, implement dynamic model training, and automate deployments with rollback options.
  • Seamless Collaboration: The series demonstrates integrating shared transformation pipelines, managing publisher/subscriber relationships, collaborating on schema/validation, and sharing and triggering transformations. It also showcases Trel's foolproof pipeline dependency visualization.
  • AI-Assisted Observability: Experience how Trel's AI-powered natural language querying provides instant insights into the CLV pipeline's operations, data quality issues, and model performance, enhancing the team's ability to understand and manage the complex data science workflow.

Getting Started Guide

  • Sign Up: Register at trelcloud.com, our PaaS portal.
  • Choose AWS Stack: Click "Create New Instance". Choose AWS option. Pick region.
  • Configure Paths: Provide a bucket and prefix for your data lake. Provide Athena database for data warehouse.
  • Specify Payment: Specify a payment method such as a credit card. You will not be charged during the Free Trial period.
  • Add credentials: Login to your dedicated Trel instance. Enter your AWS, Databricks, and OpenAI credentials.

You are now ready to add sensors to ingest data and jobs to process and export data.

TREL: DataOps and MLOps made easy

Trel DataOps vs Others

FeatureSimple CronETL SoftwareDAG Automation SoftwareDBT ToolTREL
Automation ComplexityHigh; Manually synced setupModerate; automation with some manual tuningModerate; Complex setup with some automationModerate; Configurable but primarily manualLow; automated dependency and workflow management
Resilience to Production IssuesLow; prone to frequent disruptionsModerate; some resilience but requires frequent troubleshootingHigh; robust but complex to maintain and troubleshootModerate; stable for its specific use case but not beyondVery High; minimal disruptions with quick resolution
Maintenance RequirementsHigh; constant monitoring and manual intervention neededModerate; regular updates and oversight requiredModerate; requires ongoing management of dependenciesLow; maintenance mainly involves version upgrades and dependency checksLow; self-maintaining with proactive checks
Adaptability to ChangesVery Low; rigid and difficult to modify Low; changes can be time-consuming and complexModerate; flexible but requires significant effort for modificationsModerate; changes are manageableHigh; easy to adapt and reconfigure with minimal downtime
Integration with Data Science WorkflowsNone; not suitable for data science workflowsLimited; requires external tools for full data science integrationLimited; possible but often requires custom toolingNone; primarily supports analytics, not direct data science operationsGood; seamless integration of data science tools

Introducing TREL
"The Data Engineer's Empowerment Tool"

Introducing TREL

Trel redefines data management by empowering Data Engineers with a seamless, integrated platform that transforms complex data operations into streamlined, efficient processes. It liberates engineers from the mundane tasks of data maintenance, enabling them to focus on innovation and strategic projects that propel business growth.”

Embrace Seamless Integration

Our platform is engineered to ensure that data tools not only communicate flawlessly but also synergize to enhance each other’s capabilities.

  • Simplified Workflows: Clarity in Complexity Trel’s intuitive interfaces replace confusing lines of code, making data orchestration as simple as a drag and drop.
  • Assured Data Quality: Your New Baseline With Trel, impeccable data quality becomes a baseline expectation, not just an aspirational target.

Maximize ROI with Trel

Transform Data Operations into a Strategic Asset
Release your data team from the shackles of maintenance. Trel clears the path for true innovation, empowering your experts to invest their intellect and creativity into driving business growth, not just keeping the gears turning.

Schedule a Consultation

Immediate Benefits

Strategic advancements and financial impact

Optimized Resource Allocation & Enhance Productivity

Rapid setup and maintenance of data workflows, simplifying data pipeline management and reducing complexity.

Efficient Automation

Significant reduction in operational costs through efficient automation of tasks, allowing more time for strategic development.

Reallocation of Team Efforts

Reallocation of team efforts from routine tasks to strategic initiatives.

Faster Iteration

Faster iteration on data models as teams master Trel, enabling Data Scientists to experiment with hypotheses more efficiently.

Self-Serve Capabilities

Self-serve capabilities empower Data Scientists to manage and automate data processes independently, accelerating data discovery, preparation, and experimentation for faster insights and more agile development.

Medium-Term Benefits

Sustainable Growth and Focus on Strategic Initiatives

Noticeable improvements in project delivery and team output for both Data Analysts and Data Scientists, as they can work more efficiently with streamlined data pipelines.

Data teams evolve into hubs of innovation, leveraging Trel’s efficient processes. Direct contribution of Data Engineers to strategic projects influencing business trajectory, which Data Scientists and Data Analysts can leverage to align their work with business goals

Establishment of sustainable business practices leading to a solid competitive position through better data governance and compliance, which aids in providing consistent insights.

Long-Term Benefits

Economic Impact with Tangible ROI

Drastic cuts in development time boost operational efficiency and deliver substantial savings in the long run.

Increased agility in delivering data models that directly contribute to business growth and strategic initiatives.

Scalable solutions that accommodate growing data needs, ensuring a lasting ROI.
Trel as a strategic investment in the economic resilience and future readiness of the business.

About Us

Why Work With Us

At Cumulative Data, we understand the challenges that come with managing complex data systems — from integrating disparate data sources to maintaining data quality across workflows. We know that for data teams, the difference between good and great can hinge on the right tools that make data tasks simpler and more efficient.

We’re committed to ensuring that our platform not only meets but exceeds your expectations. With Trel, you’re not just adopting a new tool; you’re embracing a partnership that grows with you.

Our robust support system and continuous product enhancements ensure that your data operations are future-proof, secure, and aligned with the latest in technology and compliance standards.

Don’t Take Our Word, Take Theirs

Contact Us

Trel automated complex data pipelines in a fraction of the time it took to build the equivalent dag in Airflow. Trel freed me from writing complex scheduling and file transfer scripts and let me just focus on the business logic. The benefit for me and my company was more time to focus on software applications and systems design. Additionally, Trel’s innovative catalog made it simple to keep track of my data.

Greg Rothman Technical Architect, Kinesso

Transform Your Data Strategy Today

We believe that every data challenge is an opportunity for innovation. With Trel, you’re not just managing data; you’re unlocking its full potential to drive your business forward.

Don’t let outdated data processes slow you down. Act now to transform your data operations.

The landscape of data management is evolving rapidly—stay ahead with Trel’s cutting-edge solutions.

Schedule Your Demo Today

See the Difference with Trel

At Cumulative Data, we understand the challenges that come with managing complex data systems.

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