Caleb Ochs Logo Caleb Ochs

Data Platform, Modeling & Power BI Consulting

Fix scattered systems, messy models, and slow reports.

I help growing teams design reliable data pipelines, clean semantic models, and Power BI reporting that leaders can trust.

Schedule a 25-minute call See how I help

Live diagnostic

Pick a scenario below and the system view shifts to show the path from scattered source systems to usable reporting.

300

projects delivered

50+

clients supported

CTO

turned consultant

Finance, operations, and executive reports do not agree.
Source systems, models, reports, and owners have sprawled.
Business logic lives in too many reports, exports, and one-off fixes.
You need senior architecture and hands-on implementation.

Services

From source systems to trusted decisions.

The best analytics work starts below the dashboard. I help teams connect source systems, clean up business logic, design usable models, and deliver reporting people can actually trust.

Data platform & pipeline buildout

Turn scattered source systems into a reliable analytics foundation.

For teams dealing with disconnected systems, brittle refreshes, manual exports, slow pipelines, or unclear ownership between source data and reporting.

  • Fabric, Azure SQL, Synapse, Data Factory, ADLS, Lakehouse, and Warehouse architecture
  • SQL-based transformation layers and repeatable data loading patterns
  • Incremental refresh, historical tracking, and pipeline reliability
  • Practical architecture that your team can maintain after the project
Talk about your data platform

Semantic modeling & metric design

Build models that make the business numbers easier to trust.

For teams where reports technically work, but definitions are inconsistent, relationships are messy, and every meeting turns into "why doesn't this number match?"

  • Star schema and dimensional model design
  • Power BI semantic models and reusable measures
  • Finance-aligned KPIs and business definitions
  • Row-level security, performance tuning, and governance patterns
Talk about modeling and metrics

Power BI rescue & reporting modernization

Fix the reporting environment you already have.

For teams dealing with slow reports, dataset sprawl, duplicated metrics, messy workspaces, licensing confusion, or legacy reports that need to move without carrying the mess forward.

  • Report and model performance tuning
  • Workspace, dataset, and governance cleanup
  • Migration from Qlik, Tableau, SSRS, Excel, or legacy reporting tools
  • Executive dashboards and operational reporting that people actually use
Talk about Power BI rescue

Fabric, Azure & AI-ready analytics

Prepare your analytics stack for what comes next.

For teams moving into Microsoft Fabric, evaluating architecture choices, or trying to make Copilot and AI summaries useful instead of vague.

  • Fabric readiness and architecture planning
  • Lakehouse and Warehouse modeling patterns
  • Copilot-friendly semantic models, measure names, descriptions, and report context
  • Clear tradeoffs between speed, scale, cost, and maintainability
Talk about Fabric or AI readiness

Engagement preview

Semantic modeling sprint

Clean up relationships, business definitions, reusable measures, and security patterns so reporting starts from trusted logic.

01

Audit

02

Model

03

Govern

04

Launch

05

Summarize

06

Operate

07

Improve

Fabric, Azure & AI-ready analytics

Power BI is the visible layer. The model underneath is where trust is built.

Fabric, Azure, Power BI, and Copilot work best when the platform, model, and business logic underneath them are clean. That means reliable pipelines, sensible architecture, clear semantic models, and reports that describe the business question they answer.

I help teams make practical architecture choices and prepare analytics models so leaders can trust the reporting today and get more useful AI summaries tomorrow.

Analytics readiness

Built for teams. Structured for AI.

Practical architecture

Fabric, Azure, Lakehouse, Warehouse, and SQL choices matched to the team's reality.

Clean semantic models

Star schemas, plain column names, clear measure names, descriptions, and logical folders.

Trusted business logic

Measures that express one business idea cleanly instead of hiding definitions everywhere.

Reports with context

Pages, visuals, titles, and descriptions that tell Copilot what the report is meant to answer.

Example executive prompt

"Summarize margin performance by region, call out unusual movement, and explain which drivers changed most."

That only works well when the model already knows what margin, region, drivers, time periods, and report context mean.

Proof

The work usually starts messy. The outcome should feel simple.

A few examples of the kinds of analytics problems I have helped teams solve across franchise, operations, manufacturing, and executive reporting.

Franchise analytics

Standardized reporting for hundreds of locations.

Migrated BI from Qlik to an Azure and Power BI platform, creating finance-aligned metrics for executives, franchise owners, and operations teams.

Service operations

Unified visibility across disconnected systems.

Designed a platform integrating SAP, fleet APIs, IFS, and other systems so leaders could understand service performance and profitability in one place.

End-to-end foundation

Built a trusted source of truth from the ground up.

Created data infrastructure and reporting across sales, inventory, distribution, and manufacturing so leadership could make decisions from the same numbers.

Process

A simple engagement path, not a consulting maze.

01. Diagnose

Clarify the real problem.

We review the current stack, reports, stakeholders, pain points, and what a better state needs to accomplish.

02. Design

Choose the practical path.

I map the target architecture, data model, governance approach, and build plan with clear tradeoffs and priorities.

03. Build

Implement with the team.

We build the models, reports, pipelines, and operating patterns so the result is useful, maintainable, and understood.

Caleb Ochs

About Caleb

Senior data help without the heavyweight consulting feel.

I am an independent consultant and former CTO who has spent the last decade working as a data engineer, architect, and analytics leader across nearly 300 projects and 50+ clients.

I am comfortable in the weeds of SQL, Power BI models, pipelines, and Azure architecture, and equally comfortable explaining to executives why a metric behaves the way it does.

Most clients do not arrive with a perfect spec. They arrive with a stack that is too slow, too scattered, or too hard to trust. That is a good place to start.