Data Analytics Consulting

Data analytics consulting that turns fragmented business data into actionable insights — building dashboards, pipelines, and predictive models that drive faster, better decisions.

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What We Do data pipeline design & executive dashboards

Assessment

Deep current-state review of your processes, data, and organizational readiness before any recommendation is made.

Strategy

A clear, prioritized plan with defined owners, milestone dates, and measurable success criteria.

Execution

Embedded support that keeps work moving — weekly standups, progress tracking, and real-time problem-solving.

Outcomes

Quantified results reported to leadership: revenue impact, cost savings, risk reduction, or capability built.

Our Process

1
Discover — Stakeholder interviews, data audit, and competitive benchmarking.
2
Design — Strategy framework and phased roadmap aligned to your goals.
3
Execute — Embedded delivery with weekly reporting and fast course-correction.
4
Transfer — Documentation and knowledge handoff for sustainable results.

Packages

Data Audit
$2,195
Current data source inventory, quality assessment, gap analysis, and analytics maturity scoring.
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Analytics Roadmap
$5,500
Data architecture design, KPI framework, dashboard specifications, and tooling recommendations.
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Analytics Suite
$9,500/mo
Full build: data pipeline, warehouse, BI dashboards (Looker/Tableau/Power BI), and ongoing model iteration.
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Frequently Asked Questions

What is a data pipeline?
An automated system that collects data from source systems (CRM, ERP, marketing tools, databases), transforms it into a consistent format, and loads it into a central warehouse for analysis — eliminating manual exports and spreadsheet chaos.
Which BI tools do you work with?
Looker, Tableau, Power BI, Metabase, and Redash — we recommend based on your team size, technical capability, and existing infrastructure. We also build custom dashboards when standard tools do not fit.
What is predictive analytics?
Using historical data patterns to forecast future outcomes — customer churn, demand forecasting, revenue projections, inventory needs. We build predictive models appropriate to your data volume and business problem.
How much data do we need to start?
Less than you think. We have built useful analytics programs for companies with 12 months of transaction data. The key is data quality and a clear set of business questions to answer, not raw volume.

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