Services
Data consulting, reporting, and automation
I help businesses fix unreliable data, connect systems that do not talk to each other, replace repetitive manual work, and build reporting people actually use. You do not need to know the technical answer before we talk, only what is not working.
A project can start with one recurring report, one dataset nobody trusts, or one process that eats a morning every week. Based in the Minneapolis-St. Paul area and working remotely.
Data Foundations
Get the data organized first.
I clean up inconsistent data, settle the business definitions everyone argues about, and build a structure that reporting and automation can depend on. This is information management and data governance without the committee.
Typical problems
- Reports from different teams show different answers
- Important fields are incomplete, inconsistent, or duplicated
- Data is spread across systems with no shared structure
What I can build
- Data cleanup, validation, and data quality processes
- Data architecture, data modeling, and agreed business definitions
- Data warehouse design and database development
- Reusable reporting layers with consistent metrics
- Data governance and information management practices
ETL & Data Integration
Get the right data where it needs to go.
If someone downloads a file from one system, cleans it up, and loads it somewhere else every week, that is a pipeline waiting to be written. I build reliable ETL and data integration between the systems a business already runs.
Typical problems
- People move the same files between systems on a schedule
- Important systems do not share data with each other
- Imports and exports fail without anyone knowing why
What I can build
- ETL and ELT pipelines using SQL and other practical tools
- Scheduled imports, exports, and SFTP workflows
- File, database, API, and system-to-system integrations
- Pipeline validation, monitoring, and error handling
Analytics, Reporting & Dashboards
Make the numbers useful.
I turn reliable data into business intelligence people actually open: dashboards, KPI reporting, and recurring financial and operational reports that show what happened, what needs attention, and where to focus next.
Typical problems
- Leaders have data but cannot quickly see what matters
- Nobody is confident that a recurring report is correct
- Teams need to explore details without rebuilding an analysis
What I can build
- Executive, financial, operational, and board reporting
- Power BI and SSRS dashboards for teams and departments
- KPI reporting, drill-through analysis, and data visualization
- Customer profitability and other business analytics tools
- Self-service reporting layers non-analysts can use
Automation & Busy-Work Elimination
Stop doing the same work over and over.
I look for the bottlenecks, repetitive tasks, and manual handoffs in a process, then automate the parts that do not need a person. The goal is less copying, reconciling, reformatting, and chasing files.
Typical problems
- A report is assembled by hand every day, week, or month
- Staff spend time reconciling, reformatting, or rekeying data
- A routine process depends on one person remembering every step
What I can build
- Automated daily, weekly, monthly, quarterly, or annual reports
- Recurring extracts, file processing, and reconciliation workflows
- Alerts and notifications when important numbers change
- Internal applications and APIs that replace manual data entry
- Business process analysis and workflow optimization
Agentic AI & Intelligent Automation
Use AI where it adds something useful.
I fix the data and the process first, then use AI for the specific work it does well: finding approved information, processing documents, or moving a research workflow along. Generative and agentic AI are tools here, not the pitch.
Typical problems
- Useful internal information is hard for employees to find
- Document review or research follows the same repeated steps
- The business sees a possible AI use case but needs a grounded plan
What I can build
- Internal assistants that use approved business information
- Document processing and repetitive research agents
- Human-in-the-loop workflows with clear review points
- Intelligent automation connected to useful internal data
Toolkit
What I build with.
The right tool depends on the problem and on what you already run. I am not trying to move you onto a new platform.
Data and databases
- SQL
- T-SQL
- Microsoft SQL Server
- PostgreSQL
- Data modeling
- Data warehousing
Analytics and reporting
- Power BI
- SSRS
- SSIS
- Python
- R
- Data visualization
- KPI reporting
Building and integrating
- Next.js
- JavaScript
- C#
- APIs
- Web scraping
- Full-stack development
Automation and AI
- Process automation
- Workflow optimization
- Generative AI
- Agentic AI
- Excel and VBA
Who this is for
Mostly small and mid-sized businesses.
Companies big enough to have real data problems but without a data team to hand them to. Usually the reporting has outgrown spreadsheets, two systems need to share information, or one person has quietly become the only one who understands how a process works.
My background is community banking, so regulated and finance-adjacent work is familiar territory: reconciliation, audit trails, board and regulatory reporting, and the habit of making numbers defensible. See the systems behind that, or look at what I build and run on my own.
A practical process
Start with what is not working.
- 01
Understand the problem
Find the data, the manual steps, the unreliable parts, and the decision the business needs to make.
- 02
Build the useful version
Clean, connect, automate, or report on the data needed to solve that problem.
- 03
Make it maintainable
Document the important logic and make the finished system understandable to the people who will use it.
Common questions
Before you reach out.
Still unsure whether your problem fits? Describe it in a couple of sentences and you will get an honest answer either way.
- What does a data consulting project usually start with?
- Almost always one concrete annoyance: a report someone rebuilds every week, a dataset nobody trusts, or two systems that will not share information. The first step is understanding how the process actually runs today, because that usually changes what should get built.
- Do I need to know the technical solution before reaching out?
- No. Describing the symptoms is enough. Knowing which report is wrong, which task eats a morning every week, or which number two teams disagree about gives more to work with than a proposed architecture.
- What size businesses is this for?
- Mostly small and mid-sized businesses that have real data problems but no in-house data team. Typically the reporting has outgrown spreadsheets, two systems need to share information, or one person has quietly become the only one who understands a process.
- Do I have to move to a new platform?
- No. The work is built around the systems you already run. The right tool depends on the problem and on your existing stack, and a platform migration is rarely the cheapest way to fix a stuck process.
- Is the work remote or on-site?
- Remote, based in the Minneapolis-St. Paul area. Data, reporting, integration, and automation work does not require being in the room, and clients outside Minnesota are common.
- What happens after the project ends?
- The important logic is documented and the finished system is built to be understandable by whoever maintains it next. The goal is work that stays useful once the engagement is over, not a system only one person can touch.
- Is experience in regulated industries relevant here?
- Seven years in community banking means reconciliation, audit trails, board and regulatory reporting, and defensible numbers are familiar territory. That habit transfers to any business where a reported figure has to hold up to scrutiny.
Start a conversation
Have a data problem that should be easier?
Whether you’re rebuilding the same report every week, working around messy data, or trying to get multiple systems to work together, let’s talk through it.