Data consulting
Data strategy, source assessment, analysis, KPI design, and reliable reporting that connects information to the questions your organization needs to answer.
Clear data foundations and decision-ready insightPractical intelligence, thoughtfully delivered
SA Data helps small and medium-sized businesses and public-sector teams turn complex information into clear decisions, useful automation, and reporting people can trust.
Canada-based consulting · Clear scope · Practical outcomes
Consulting services
We start with the decision or operational problem, then use the lightest practical combination of data, AI, and reporting to solve it.
Data strategy, source assessment, analysis, KPI design, and reliable reporting that connects information to the questions your organization needs to answer.
Clear data foundations and decision-ready insightPractical AI prototypes and workflow automation designed around your team, with human review, clear boundaries, and a path from experiment to useful operation.
Less repetitive work, with people in controlDashboards, performance measures, data models, and executive reporting that make results easier to understand, explore, and act on.
A shared view of performance and prioritiesSelected work
Two focused demonstrations of how SA Data approaches automation and public data.
A focused prototype for turning spoken job details into a structured, reviewable quote draft for plumbing, HVAC, construction, and field-service teams.
Explore the prototypeA data-driven demonstration that brings official economic and community indicators into one searchable, transparent portal with source and quality context.
View the MVPExperience
More than 14 years of experience across higher education, financial services, insurance, consumer goods, and food manufacturing informs a practical, adaptable consulting approach.
Developed Python-based exercises for undergraduate business administration courses, using LLM and RAG workflows grounded in official management and business textbooks.

Designed SQL Server star-schema models and developed Power BI dashboards and business reports.

Developed Power BI dashboards and reports with Microsoft 365 data and workflow integration.
Built a near-real-time Azure Databricks pipeline in PySpark and Python, moving Parquet data from AWS S3 to ADLS Gen2 in 15-minute micro-batches with medallion architecture, aggregation, reconciliation, and validation.

Performed Python-based analysis of electrical spikes in plant equipment, profiling frequency, duration, patterns, and magnitude while comparing energy intensity against production throughput during startup and normal operation.
Organization names and marks are shown only to identify professional experience; no endorsement is implied.
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