Data engineered into operational insight.
Unify sources. Model the business. Put trusted numbers in front of the people making decisions — without a six-month warehouse rebuild. Six weeks to first dashboard. Lineage and freshness wired in from day one.
What we deliver.
Six capabilities. One delivery shape. Strategy through governance — engineered so the numbers the business runs on can be trusted by default.
Data analytics fails when the numbers leadership uses cannot be trusted. We deliver the full analytics stack — from data collection and preparation through advanced analysis and insight generation — engineered against the operating decisions the business actually makes. Tests, lineage, and freshness are part of the pipeline. Not an afterthought.
Data Strategy and Planning
Senior architects partner with the business to develop a data strategy aligned to operating objectives. Existing infrastructure assessed. Source map produced. Governance framework defined — covering quality, consistency, and access control.
Data Integration and Management
Sources connected. Formats harmonized. Estate managed at rest and in motion. Analysts work from a single source of truth — not a maze of forks.
Data Analysis and Insights
From exploratory analysis to executive dashboards — raw signal engineered into the insights leadership actually uses to set direction.
Visualization and Reporting
Dashboards, scorecards, and self-serve patterns built around the questions the business actually asks — not the screenshots from the vendor demo.
Predictive Analytics and ML
Forecasting, churn, propensity, anomaly detection. Production-grade models tied to the workflow KPI. Evaluation harness and retraining cadence built in.
Data Governance and Compliance
Lineage, access control, retention, and audit trail wired into the same pipeline that delivers the dashboards. Compliance evidence falls out — not bolted on.
Data engineered into operating decisions. Trusted by default. Governed continuously. Owned by the team that runs the business.
Trusted by default
Tests, freshness, and lineage wired in.
Fast to first metric
Reusable models · 6 weeks to first dashboard.
Warehouse-agnostic
Same patterns on Snowflake, BigQuery, Redshift.
Stewarded
Documentation and ownership baked in.
What's in the box.
Capabilities included in the standard Data Analytics rollout — modular, swappable.
Ingestion
- Source connectors
- CDC and batch
- PII handling
Warehouse
- Layered modeling
- Cost guardrails
- Workload tuning
Transformation
- dbt projects
- CI tests
- Reusable macros
BI and semantics
- Looker / LookML or Power BI
- Metric layer
- Self-serve patterns
Activation
- Reverse ETL
- Audience segmentation
- ML feature export
Governance
- Lineage
- Access control
- Data contracts
Tools we bring.
An opinionated default stack — swap any of it for what your team already runs.
What you actually get on day 90.
Data Analytics in the field.
Posts, trends, and client stories tied to Data Analytics.
See how Data Analytics fits your stack.
30 minutes with a senior engineer — we'll tell you what we'd do.