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PRACTICE / TECHNOLOGY

Insight is the byproduct. Action is the product.

Data platforms that turn analytics into action.

We build the data layer companies actually use — ingestion, governance, modelling, and self-serve analytics — so the business stops debating the numbers and starts moving on them.

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  1. 01Data Management & Integration
  2. 02Data & Business Analytics
  3. 03Data Governance & Compliance

  1. Data Management & Integration

    Centralize, organize, and ensure high-quality, accessible data across platforms.

    DELIVERED WITHFivetran · Airbyte · dbt

  2. Data & Business Analytics

    Deliver predictive analytics, reporting, and interactive dashboards.

    DELIVERED WITHLooker · Tableau · Mode

  3. Data Governance & Compliance

    Implement strong governance and auditing, and ensure regulatory compliance.

    DELIVERED WITHCollibra · Alation · Atlan

  4. Cloud Data Solutions

    Scalable, secure cloud storage, backup, and data-processing integration with AWS, Azure, and more.

    DELIVERED WITHSnowflake · Databricks · BigQuery

  5. Data Migration Services

    Secure, seamless data migration with minimal downtime and zero data loss.

    DELIVERED WITHAWS DMS · Striim · Debezium

  6. Big Data & Data Quality

    Handle large datasets and real-time insights, and ensure clean, consistent, reliable data.

    DELIVERED WITHSpark · Kafka · Great Expectations

02 / ENGAGEMENT SPINE

How a data engagement actually runs.

Five phases — each with a clear deliverable so the progress is checkable, not vibes. Phases overlap in practice; the rail is sequence, not gates.

  1. 01

    Discover

    Profile sources, contracts, and the decisions data is meant to support. Identify quality and latency requirements.

    • Source profile
    • Decision map
    • SLA matrix
  2. 02

    Design

    Model the warehouse, the semantic layer, and the governance posture. Define ownership for every dataset.

    • Dimensional model
    • Semantic layer
    • Ownership map
  3. 03

    Engineer

    Build the pipelines — ingestion, transformation, quality tests, and the BI surface. Documentation as you go.

    • Pipelines
    • Quality tests
    • BI dashboards
  4. 04

    Deploy

    Roll out to first-party consumers with shadow runs and parallel reconciliation. No silent cutovers.

    • Shadow run
    • Reconciliation
    • Stakeholder signoff
  5. 05

    Operate

    Steady-state observability, lineage tracking, and quarterly cost-and-quality review.

    • Observability
    • Lineage
    • Quarterly review

03 / TOOLCHAIN

What we reach for on data engagements.

Tools are choices, not commitments — substitute per your environment. The grouping below is the shape of the stack, not a vendor list.

WAREHOUSE

  • Snowflake
  • BigQuery
  • Databricks
  • Redshift

INGESTION & TRANSFORM

  • Fivetran
  • Airbyte
  • dbt
  • Apache Spark

STREAMING

  • Kafka
  • Kinesis
  • Confluent
  • Flink

BI

  • Looker
  • Tableau
  • Mode
  • Hex

GOVERNANCE

  • Collibra
  • Atlan
  • DataHub
  • Great Expectations

Bring your data brief.A principal responds within one business day.

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