Marketing analytics. Governance. Customer intelligence.

I turn messy business data into decisions people trust.

I am John Johannaber, an analytics leader with 10+ years across data quality, customer analytics, BI, fraud prevention, CRM data, and stakeholder enablement.

John Johannaber
John Johannaber, MSMarketing analytics, governance, BI, and customer-data problem solving.
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Proof signalsAtlanta, GA
200M+records governed through SQL and Python quality rules
78%fraudulent transaction reduction in a cross-functional prevention program
20% -> 1%email bounce-rate improvement after customer-data remediation
$100K+direct-mail campaign revenue supported through analytics and targeting
Advanced SQLPython automationMarketing analyticsCampaign measurementBI dashboardsMetadata and lineageExecutive-ready storytelling

Selected projects

Work that moves numbers, not just charts.

Fraud analytics

Dormant-account deactivation engine

$390K R12 fraud reduction

Proposed and drove an analytics initiative after identifying account takeovers as a preventable risk. Analyzed 992 prior incidents, found dormant-account patterns, automated monthly targeting, and coordinated notification and deactivation workflows.

  • 3.6M accounts deactivated
  • 64% email open rate
  • 4 complaints across the program
SQL, Python, segmentation, stakeholder reportingView deck

Data quality

Enterprise data-quality engine

100+ rules across 200M+ records

Translated business definitions into executable quality checks, automated monitoring, and Tableau reporting for high-volume customer and marketing repositories. The work made downstream campaigns and reporting more trustworthy.

  • Completeness, validity, uniqueness
  • Python automation
  • Tableau monitoring
SQL, Python, Tableau, Collibra, customer data

Marketing analytics

Campaign intelligence and customer-data lift

Bounce rate improved from 20% to 1%

Improved the customer data powering marketing campaigns, built reporting for direct-mail and digital channels, and helped teams understand buying patterns, campaign performance, and customer engagement.

  • Channel effectiveness reporting
  • Forecasting and trend analysis
  • $100K+ campaign support
SQL, Power BI, Tableau, ETL, customer segmentation

Identity resolution

Company matching ETL proof of concept

Fuzzy matching plus address standardization

Built a tactical identity-resolution workflow for duplicate company records across incoming files and CRM exports. Compared a fast Python approach with enterprise-grade vendors for scale, support, and long-term fit.

  • Threshold-based entity grouping
  • Vendor tradeoff analysis
  • Reusable ETL logic
Python, Pandas, fuzzy matching, CRM dataView deck

Public BI

Lights, Camera, Analytics

Interactive Tableau film dashboard

Modeled IMDb title, principal, name, and rating tables to analyze 30 years of movie trends across genres, runtime, ratings, actors, and annual patterns.

  • IMDb public data
  • Calculated metrics
  • Tableau dashboard
Tableau, data modeling, metric designOpen dashboardView deck

Project decks

More of the thinking, structure, and presentation style.

Fraud prevention analytics deck cover

Fraud prevention analytics

Cross-functional account-takeover analysis, dormant-account targeting, funnel reporting, and R12 impact.

Open PDF
Identity resolution ETL deck cover

Identity resolution ETL

Python proof of concept for company matching, address standardization, fuzzy thresholds, and vendor tradeoffs.

Open PDF
Lights, Camera, Analytics deck cover

Lights, Camera, Analytics

Tableau documentation for IMDb data modeling, transformations, calculated metrics, and dashboard design.

Open PDF

Experience

From campaign analytics to enterprise data trust.

2026 - Present

Data Governance Analyst

Guild Mortgage

Building governance standards, metadata clarity, process documentation, and a data-quality engine for critical mortgage data.

  • Develop data-quality rules and monitoring for critical mortgage data.
  • Partner with business and technical teams on metadata, definitions, and governance standards.
  • Built a custom GPT that turns process notes into standardized flow diagrams.
2025 - 2026

Data Analyst Contractor

Independent

Unified Salesforce CRM, admissions, and enrollment data in AWS Athena for universities and delivered cloud, quality, and reporting work across multiple client domains.

  • Unified Salesforce CRM, admissions, and enrollment data for three universities in AWS Athena.
  • Built applicant-to-admission metrics to help predict future-term engagement.
  • Delivered data-quality checks, QuickSight reporting, and migration standards across client projects.
2020 - 2025

Senior Analyst, PI Data Management and Quality

The Home Depot

Led customer-data quality, lineage, vendor evaluation, privacy, marketing-data remediation, and enterprise reporting initiatives.

  • Translated 100+ data-quality rules into SQL and Python across repositories with 200M+ records.
  • Improved email-campaign data quality enough to reduce bounce rates from 20% to 1%.
  • Partnered with marketers, privacy attorneys, engineers, survey teams, and data managers on customer-data use.
2019 - 2020

Analytics Engineer

AnswerRocket

Owned data validation, client go-lives, dashboards, training, and analytics delivery for enterprise SaaS customers.

  • Led go-live validation for enterprise clients with contracts up to $25K per month.
  • Built dashboards and data visualizations for GE Automotive and other customers.
  • Translated requirements into customer-specific reporting, documentation, and training.
2017 - 2019

Marketing Database Analyst

Purchasing Power

Built marketing BI, campaign reporting, forecasts, and ETL workflows that helped stakeholders evaluate direct-mail and digital-channel performance.

  • Produced BI reports to forecast buying patterns and monitor campaign performance.
  • Created year-over-year dashboards with monthly and weekly drill-down views.
  • Automated ETL processes to improve reporting speed, accuracy, and repeatability.
2016 - 2017

Data Analyst

MarkeTeam

Developed data-integrity algorithms, SQL architecture, and BI reporting for regression-based direct-mail campaigns for national nonprofits.

  • Supported direct-mail campaigns generating more than $100K each.
  • Improved SQL data architecture for campaign data loading and analysis.
  • Integrated VBA macros, SSIS packages, SQL Server, and Power BI into analytics workflows.
2014 - 2015

Data Science Intern

CloudTags

Produced retail reporting and SQL-based analysis for a data-collection company while coordinating with clients and senior leaders.

  • Built daily and weekly statistical reporting for retail data-collection projects.
  • Created SQL queries, procedures, and functions for Excel-based reporting.
  • Helped refine project specifications with clients and internal leaders.
2023 - Present

Adjunct Instructor and Python Instructor

SNHU and Masterschool

Teach analytics foundations, Python, data verification, privacy, ethics, and open-source tooling to graduate and professional learners.

  • Teach a master's-level Foundations of Data course to roughly 30 students per term.
  • Taught Python fundamentals, data processing, and data manipulation to 50 analytics students.
  • Bring complicated technical topics down to practical, usable explanations.

Toolbox

Technical enough to solve it. Clear enough to sell it.

My lane is where business questions, flawed data, and operational pressure meet: defining the metric, finding the issue, building the workflow, and making the answer usable for the people who need it. A lot of that work has lived in customer and marketing analytics: campaign performance, segmentation, buying patterns, email data, direct mail, CRM data, and engagement metrics.

SQLPythonTableauPower BIQuickSightAWS AthenaSalesforce dataData qualityIdentity resolutionGovernanceMarketing analyticsCampaign reportingCustomer segmentationForecastingDirect-mail analyticsCustomer analyticsFraud analytics

Let us make the data useful

Hiring for marketing analytics, governance, or customer-data work?

I bring the rare mix of SQL depth, stakeholder fluency, quality discipline, and dashboard instincts that turns a fuzzy data problem into a business decision.

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