Data & Analytics

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What We Offer

We run data and analytics platforms through a single orchestration layer that ensures data is reliable, metrics are consistent, and insights are operationalized across the business.
Our services scale from foundational implementations to fully managed analytics operations.

Our Orchestration Platform
A managed execution engine that runs automations and integrations under a fair-use model. Billed separately from service subscriptions unless the client owns the platform.

  • Modern data stack foundation

    For teams standing up or rebuilding their analytics foundation.

    • Data stack architecture and platform selection

    • Event tracking and data ingestion setup (CDP, pipelines)

    • Cloud data warehouse implementation

    • Core data pipelines from source systems

    • Initial data models and transformations

    • BI tool setup and baseline dashboards

    • Testing, documentation, and handoff

    Outcome:
    A production-ready data stack with clean ingestion, a central warehouse, and trusted initial reporting.

  • End-to-end data orchestration

    For teams scaling analytics across multiple sources and teams.

    • Multi-source data ingestion and pipeline orchestration

    • Data transformation and metrics modeling

    • Product and behavioral analytics integration

    • Reverse ETL to operational systems

    • BI semantic layer and metrics governance

    • Data quality rules and validation

    • Monitoring, alerting, and lineage documentation

    Outcome:
    Analytics platforms operate as a coordinated system, with consistent metrics and reliable data flow end to end.

  • Managed data operations & reliability

    For organizations that need analytics to stay accurate and trustworthy over time.

    • Ongoing data pipeline operations and support

    • Proactive monitoring of freshness, volume, and schema changes

    • Incident response and root cause analysis

    • Continuous model and dashboard optimization

    • AI agents for anomaly detection, data health insights, and triage

    • Change management for new sources, metrics, and teams

    • Quarterly data platform health reviews

    Outcome:
    Data is reliable, governed, and trusted by leadership and operators.

  • Enterprise-scale analytics orchestration

    For complex, regulated, or high-volume environments.

    • Custom data and analytics architectures

    • Enterprise data governance and cataloging

    • Advanced observability and data reliability programs

    • Cross-region, multi-warehouse strategies

    • M&A data consolidation and migration

    • Security, compliance, and audit readiness

    • Dedicated data delivery and operations pods

    Outcome:
    A long-term analytics operations partner for mission-critical data environments.

Our Process

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Optematic Foundations

Discovery, Analysis, and Execution Planning

This phase exists to remove ambiguity before anything is built.

Optematic Foundations is the structured discovery and planning phase that defines what will be built, why, and how it will operate once live. It is business analyst and project management focused, designed to translate business needs into executable technical work.

What this phase covers

  • Business process discovery and stakeholder interviews

  • Current state system and process documentation

  • Future-state system and process design

  • Requirements definition and user story creation

  • User story grooming and prioritization

  • Integration and automation opportunity analysis

  • Technical approach, assumptions, and constraints

  • Delivery plan, milestones, and success criteria

Primary roles involved
Business Analysts, Project Management, Solution Architecture

Output
A complete, build ready backlog and delivery plan with clear scope, acceptance criteria, and operational intent.

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Optematic Build

Implementation, Validation, and Launch

This phase turns approved requirements into working systems.

Optematic Build is the execution phase where systems, integrations, and workflows are implemented, tested, and prepared for production. It is developer and QA heavy, focused on delivering stable, production ready functionality.

What this phase covers

  • System configuration and development

  • Integration and workflow implementation

  • Proofs of concept where required

  • Unit testing and system testing

  • User acceptance testing (UAT) support

  • Defect remediation and refinement

  • Deployment planning and production release

  • Knowledge capture for ongoing operations

Primary roles involved
Developers, QA Engineers, Solution Architects

Output
Live, production grade systems and integrations that meet defined acceptance criteria.

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Optematic Automate

Monitoring, Optimization, and Reliability Operations

This phase ensures what was built actually runs.

Optematic Automate represents the transition from project delivery into operational ownership. The focus is on monitoring, tuning, and stabilizing systems so they perform reliably under real world conditions.

What this phase covers

  • Integration and automation monitoring

  • Error handling, alerting, and incident response

  • Performance tuning and reliability improvements

  • Automation refinement based on usage patterns

  • Operational runbooks and escalation paths

  • Minor fixes and adjustments post launch

Primary roles involved
Automation Engineers, Support Engineers, Ops-focused Developers

Output
Stable, monitored, and optimized automations and integrations that run consistently.

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Optematic Managed

Continuous Improvement and Long Term Partnership

This phase is where ongoing value is created.

Optematic Managed is the long term managed services layer focused on identifying improvements, expanding capabilities, and evolving systems as the business changes. This is not reactive support, it is proactive, roadmap driven partnership.

What this phase covers

  • Ongoing system and automation management

  • Identification of new automation and integration opportunities

  • Enhancement backlog creation and prioritization

  • Continuous delivery of improvements

  • Platform expansion and new system onboarding

  • Advisory support aligned to business goals

Primary roles involved
Systems Architects, Automation Engineers, Delivery Leads

Output
Continuously improving systems that evolve with the business without requiring internal headcount growth.

  • “They put a real orchestration layer around our data stack. Pipelines stopped breaking silently, schema changes were controlled, and we finally had a clean way to scale analytics without creating chaos.”

  • “Before this, we didn’t trust our numbers. By centralizing how data flows and is governed, they gave us consistent metrics and confidence in the reporting we use to run the business.”

  • “They connected product, revenue, and finance data into one coordinated analytics system. Reporting became faster, cleaner, and actually useful for decision-making across teams.”

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Let’s Work Together

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