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Independent Business Intelligence Consulting

Turn your data into decisions leaders act on.

Senior BI leadership for teams whose data is scattered, slow, or hard to trust. I set data and AI strategy, build dashboards executives use, automate the reporting behind them, and support your team long after launch.

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Sample Power BI story page titled Three properties drive 71% of the cost increase, with KPI cards, a bar chart by property, and a monthly cost trend
Sample Power BI story page, built for a fictional company.

Since 2005

Working in data, from analyst to BI Manager

Diverse, high-performing teams

Led analysts, data engineers, and BI developers

Power BI, Fabric, Databricks

The Microsoft data stack, end to end

Services

My work falls into four areas, from setting data and AI direction to keeping reporting running. Most clients start with one of the featured packages below.

01

Strategy & Leadership

Data and AI strategy, readiness assessments, governance, and implementation roadmaps.

  • Data strategy
  • Fractional BI leadership
  • KPI definition
  • Governance foundations
  • AI readiness & roadmaps

02

Dashboards & Insights

Decision-focused reporting, AI-assisted insights, and performance measurement for AI solutions.

  • Power BI builds
  • Dashboard redesign
  • Executive reporting
  • Analytics storytelling
  • AI performance measurement

03

Data & Automation

Reliable data workflows, AI-enabled automation, and practical business tools.

  • Reporting automation
  • Data preparation
  • Data quality
  • Fabric & Databricks planning
  • AI-enabled automation

04

Support & Enablement

Ongoing help so your team can keep the work running.

  • Managed BI support
  • Training
  • Documentation
  • Analytics office hours

Featured packages

Defined starting points, each with a clear deliverable and a handoff your team can run with.

Strategy & Leadership

Package 01

Data Strategy

A clear plan for your data: what to measure, who owns it, and what to build first, so analytics spending goes where it pays off.

  • Stakeholder interviews and a current-state review
  • KPI definitions with owners, formulas, and sources
  • A prioritized roadmap and build-ready backlog

Best for: organizations about to invest in analytics but unsure what to build, or whose departments report conflicting numbers.

Package 02

Fractional BI Leadership

Senior analytics leadership without a full-time hire, offered as a monthly retainer sized to your needs.

  • Weekly leadership meetings and backlog prioritization
  • An analytics roadmap, refreshed every quarter
  • Monthly executive updates and oversight of your team or vendors

Best for: growing companies that need a BI leader but aren’t ready to hire one full time.

Dashboards & Insights

Package 03

Power BI Audit & Optimization

A structured review of your reports, semantic models, and refresh pipeline, ending in a prioritized plan to make them faster, leaner, and easier to trust.

  • Data model, DAX, and refresh performance review
  • Report design, usability, and governance check
  • Findings report with prioritized fixes and quick wins

Best for: reports that load slowly, disagree with each other, or only one person knows how to maintain.

Package 04

Executive Data Storytelling

Dense dashboards, reshaped into a clear story for leadership: the few measures that matter, what changed, and what to do about it.

  • KPI focus and audience mapping with stakeholders
  • Executive-ready report pages and briefing layout
  • Storytelling guidelines your analysts can reuse

Best for: leaders who have dashboards but still ask for the slide deck.

Package 05

Power BI Dashboard Build

A new Power BI dashboard built on the data you already have, from cleanup and modeling to a published report your leadership team will use.

  • Discovery of the decisions, audience, and KPIs it supports
  • Power Query cleanup, star-schema model, and DAX measures
  • Published report with documentation and a walkthrough

Best for: teams with data in spreadsheets, SQL, SharePoint, or Fabric, but no dashboard leaders rely on.

AI offers

Package 06

AI Opportunity & Readiness Assessment

Decide which AI ideas are worth pursuing, and what your data, governance, and licensing need before you start.

  • Stakeholder interviews and up to 10 candidate use cases
  • Each use case scored on value, feasibility, data readiness, and risk
  • A 90-day roadmap, responsible-use guidelines, and one or two pilot picks

Best for: leadership teams under pressure to adopt AI without a clear place to start.

Package 07

AI Solution Discovery & Pilot

Validate one bounded use case with real users before you commit to a production build.

  • Discovery of the use case, data, users, and success measures
  • A working pilot in your own Microsoft tenant for a small user group
  • Accuracy testing, user feedback, and a go, extend, or stop recommendation

Best for: teams with a promising AI idea that needs proof before a larger investment.

Package 08

AI Performance & Value Dashboard

A Power BI dashboard that shows whether your AI solutions are paying off: quality, adoption, cost, and business outcomes.

  • Agreed definitions for quality, adoption, cost, and value
  • Data drawn from usage logs, user feedback, and licensing or consumption
  • A published report with targets and a monthly review routine

Best for: organizations running copilots, chatbots, or agents without a clear view of what they return.

Need something from another area, or not sure where to start? Every engagement begins with a 30-minute call.

Book a 30-minute call

How an engagement works

Fixed scope, regular check-ins, and documentation built in, so the work keeps paying off after I’m gone.

01

Discovery call

A conversation about your reporting, who relies on it, and the decisions it needs to support. You’ll leave knowing which engagement fits, if any.

02

Scope and build

A written scope, timeline, and deliverables, then hands-on work in your Power BI, Fabric, or Databricks environment.

03

Handoff

A walkthrough with your team, documentation of what changed and why, and recommended next steps, so you can maintain it without me.

Case studies

Four anonymized engagements, from measuring capacity and automating onboarding to redesigning dashboards leaders actually use.

Case study 01

An engagement dashboard that showed leaders where to act

Survey results are only useful if leaders can see where to act. This dashboard turned annual and pulse survey results into a view executives could use by market, region, and department.

Before and after chart makeover: a cluttered 40-bar chart replaced by a ranked bar chart titled 3 properties drive 71% of the cost increase
Sample chart makeover from my portfolio, using data for a fictional company. The client dashboard isn’t shown.

The challenge

A large property-management organization ran annual engagement and pulse surveys, but leaders had no clear way to see where satisfaction was strong or slipping.

What was built

A Power BI dashboard of satisfaction measures by market, region, and department, designed for senior executives rather than analysts.

The result

Executives used it to focus improvement efforts where they mattered most and to support employee retention.

Case study 02

A chatbot dashboard that showed where to grow adoption

A customer-service chatbot had a Power BI dashboard no one could read at a glance. A redesign grounded in stakeholder discovery made it the view leadership used to track the platform and decide where to roll it out next.

Report structure after the redesign

  1. Executive Overview Key metrics from every page in one view
  2. Engagement How customers interact with the chatbot
  3. User Insights Who uses it and what they ask about
  4. Adoption & Reach Growth across properties and regions
  5. Operations Performance and service metrics

One crowded page became five focused pages with menu navigation. The client dashboard isn’t shown.

The challenge

The original dashboard was built before the Product team and business owners had defined what they needed to know. It was one crowded page, and leadership couldn’t quickly tell whether the chatbot was working.

What was built

After discovery sessions with Product and the business owners, the report was rebuilt as five focused pages, led by an Executive Overview that brings the key metrics from each page together.

The result

The dashboard exposed conversation types the platform wasn’t recording, which led to an app fix. It also showed the chatbot was cutting support calls mostly at low-volume properties, so rollout shifted to the properties and regions with the most calls.

Case study 03

A capacity model that showed leaders when to hire

Senior leaders at a professional services firm couldn’t tell whether they had enough accountants for the work coming in. A capacity model and dashboard gave them one shared measure of workload and a clear signal for when new sales meant new hires.

How the capacity model works

  1. Available days Working days minus planned time off, based on each accountant’s seniority
  2. Client complexity Each account scored and weighted by the work it creates
  3. Monthly capacity Load against capacity for every accountant, month by month
  4. Hiring signal The point where pipeline work passes available capacity

A simplified view of the model. The client dashboard isn’t shown.

The challenge

There was no consistent way to measure how much work one accountant could carry in a month, and no signal for when incoming work called for hiring. Staffing decisions were reactive, especially at peak periods and after new deals closed.

What was built

After discovery with client accounting leaders, HR, and Sales, I built a client complexity matrix and a monthly capacity measure for each accountant, adjusted for seniority-based time off. A Power BI dashboard compared load to capacity and connected to the sales pipeline.

The result

Leaders could rebalance work before peak deadlines slipped, assign new clients consistently, and see when projected work would pass available capacity, so they could make the case for new hires with data.

Case study 04

An onboarding agent that gave hiring managers their time back

New hires were set up with accounts and equipment, but nothing introduced them to their team. An AI agent sent team-specific welcome information and scheduled introductions automatically, and a chatbot built on the team’s knowledge base gave new hires a place to ask questions. Hiring managers could then spend their one-on-one time on real training.

How team onboarding works

  1. Hire confirmed A form with the new hire’s name, email, and start date triggers the onboarding agent
  2. Welcome email Team-specific essentials: org chart, key contacts, and where to find things
  3. Introductions scheduled Meetings booked with the people the new hire needs to know
  4. Ask the chatbot in Teams Answers drawn from the team’s org charts, SOPs, and documentation

A simplified view of the workflow. Client systems aren’t shown.

The challenge

Company-wide workflows handled security groups and equipment such as laptops and monitors, but nothing covered the team a new hire was joining. Hiring managers repeated the same work for every hire: walking through the org chart, scheduling introductions, and answering routine questions about how the team worked.

What was built

When a form confirms a new hire’s name, email, and start date, an AI agent sends them key team information and schedules their introduction meetings through Outlook and Teams. A Copilot Studio chatbot built on the team’s SharePoint knowledge base (org charts, SOPs, and documentation) answers their questions in Teams whenever they come up. Built with Copilot Studio, Power Automate, SharePoint, Outlook, and Teams.

The result

Hiring managers spent less time on repeat explanations and more on focused, one-on-one training. New hires had a reliable reference from day one. The chatbot supported the manager relationship rather than replacing it.

Daphne Champagne, founder of Winged Data

About

Meet Daphne Champagne

Founder and principal consultant, Winged Data LLC

I’ve worked in data since 2005, growing from data analyst to Business Intelligence Manager. In that role I led a 20+ person team of analysts, data engineers, and BI developers, and saw firsthand how faster, clearer reporting changes the way leaders make decisions.

When you work with Winged Data, you work directly with me: someone who has owned BI end to end, from the data model to the conversation with leadership. It’s senior expertise without a full-time hire. I’m based in Northern Colorado and work with clients remotely.

Power BI

Microsoft Fabric

Azure Databricks

DAX & data modeling

Executive reporting

Let’s talk about your data.

Tell me what’s slowing your reporting down. In one 30-minute call, we’ll work out where you need help, whether that’s strategy, dashboards, data and automation, or ongoing support. Pick a time that works for you.

Book a 30-minute call