Omnificity

Chief Executive Officer

Founder

Handora

Datinuum

Covering the full continuum of data.

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Founder and Chief Creator

Various Companies

Chief Data Officer

Eastern Bank

VP, Business Intelligence Architecture

Inspire11

Senior Management Consultant

Management Consultant

Court of Opinion

Founder and co-host of weekly sports podcast that focuses on the NBA.

Founder and Co-Host

Trexin Consulting

Principal Management Consultant, Data Analytics Lead

Associate Management Consultant

R1 RCM

Business Intelligence Lead Analyst

Intermedia Touch- Digital Signage Integrator

Software Project Manager

Eric Gonzalez is a skilled data executive with experience in financial services, healthcare, agriculture, and education.

Eric is the founder and CEO of Omnificity, an executive advisory firm, where he serves as a trusted advisor to companies ranging from early-stage startups to Fortune 500 companies, providing expert guidance on data best practices.

Eric has worked in hundreds of departments across 25+ organizations, collaborating with executives and leadership teams to optimize their data solutions and help them make data-driven decisions.

In his various roles, Eric has led and coached product teams to help organizations evangelize solutions, migrate to new platforms, develop product roadmaps, and build their analytics infrastructure. Eric's work has helped clients drive operational improvements and achieve significant cost-savings, with one engagement resulting in a $200M+ turnaround year-over-year.

His strong leadership and management skills have enabled him to manage cross-functional teams and drive the product development lifecycle.

Throughout his career, Eric has consistently mentored and developed junior employees, helping them to grow professionally.

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Functional: Agile Methodologies, Business and IT Alignment, Business Development, Business Strategy, Change Management, Communication, Cross-functional Collaboration, Customer Experience, Data & Analytics Strategy Development, Data-driven Growth, Decision Making, Executive-level Communication, Opportunity Identification, Operational Model Development, People Development, Product Development, Project Management, Solution Design, Stakeholder Management, Strategic Planning & Growth, Team Building, Technical Product Management

Technical: Advanced Analytics, Artificial Intelligence (AI), Automation, Big Data, Business Intelligence, Cloud-based Environments, Data Analytics, Data Architecture, Data Engineering, Data Enrichment, Data Governance, Data Integration, Data Modeling, Data Pipelines, Data Quality, Data Science, Data Storage, Data Visualization, Enterprise Data Management, ETL / ELT, Machine Learning, Predictive Modeling, Statistical Methods

Tools & Technologies: AWS, Azure, Databricks, dbt, Jira, Looker, Power BI, R, Snowflake, SQL, Tableau

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I love networking and connecting with others. If you want to chat about the newest tech or how this is the year the Hurricanes will make it to a national championship, please reach out!

My posts are my own and don't reflect the opinions of my current, past, or future employers.

Follow #EGDataGuy for all my content!

If your analysis always supports what your boss wants to hear, you're not doing analysis, you're doing p-hacking. And it's going to wreck your career.

Nobody explains this early on, but there's a common trap to watch out for.

CXO has an idea they're excited about. Asks you to analyze whether it's good. You want to be helpful and make them happy. So you focus on data that supports their idea and downplay stuff that contradicts it. You present your findings in a way that makes them look smart. Everyone's happy...until the idea fails and you realize you helped them make an expensive mistake.

The scientific method your middle school teacher taught you applies to business:

1. Make observations. 
2. Form hypotheses. 
3. Test them with data that could prove you wrong. 
4. Accept the results even if they contradict what you wanted to find. 
5. Repeat.

This isn't complicated, but somehow, businesses keep forgetting it.

The skill that separates good analysts from mediocre ones is intellectual honesty with data. Before starting analysis, write down: "I think X is true. Here's how I'll test it. Here's what would prove me wrong." Then actually follow through. If data says you're wrong, say so clearly. Don't hunt for different data or different ways to slice it until you get the answer you wanted.

Regardless of where you are in your career, build a reputation as the person who tells the truth, not the person who makes stakeholders feel good. This is scary early in your career when you want people to like you. But in the long term, people trust and promote analysts who are right, not those who are agreeable.

If someone asks you to "prove" something instead of "test" something, they want confirmation, not discovery. If you find yourself excluding data because it's "inconvenient," you're p-hacking. If your analyses always support stakeholder preferences, you're not being intellectually honest.

The analysts who advance are those who can tell leadership, "your hypothesis is wrong, here's what the data actually show" without making it personal. 

Learn that skill now.

#EGDataGuy

Eric Gonzalez

Fractional CDO & Executive Advisor | Translating Complex Analytics into Boardroom Decisions | Husband, Father, Creator

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