Xavier Veloso | Portfolio

Hey, I’m Xavier.
Data Analyst Based in The Philippines.

I build dashboards, uncover patterns, and turn messy business data into clear insights. My work focuses on analytics, reporting, database management, and research-driven problem solving.

View Projects Contact Me

SQLData cleaning, joins, automation, QA

BIDashboards, reporting, storytelling

ResearchAnalysis for real estate and business use

About Me

I’m Xavier Veloso — a forward-thinking data and business intelligence professional with experience helping organizations turn data into strategic insights and impactful decisions. I design and implement data solutions that empower cross-functional teams to visualize performance trends, streamline reporting processes, and unlock actionable insights from complex datasets. I specialize in transforming raw data into polished dashboards and meaningful analytics that support organizational goals and drive better outcomes.

📊 Data Analytics

Exploring datasets, finding trends, validating data quality, and building actionable reporting.

🗄️ Database Management

Working with structured data, SQL workflows, automation, and reliable data pipelines.

📈 Business Research

Supporting decisions through market research, operational analysis, and domain-specific insights.

Experience Highlights

Jan 2024 – March 2026
Colorado, United States
· Remote

CRM & Data Analyst

Colorado Ranch and Land Brokers

• Collected, transformed, and analyzed land and ranch properties dataset that are worth $2,000,000+, are 500+ acres and within Colorado, from various sources including MLS, real estate marketplaces, state public records, and proprietary databases. The data was stored in the Airtable database.
• Managed and maintained the FollowUpBoss CRM database with 25,000+ contacts, ensuring efficient data storage and retrieval. Profiles were created from the CRM analysis to be used as guides for targeting hot leads.
• Prepared comprehensive reports, visualizations, and dashboards to communicate findings and recommendations to stakeholders using Airtable and Excel.
• Developed and maintained statistical models and predictive analytics to forecast market trends, property values, and investment opportunities for land and ranches within Colorado.
• Continuously monitored data quality and integrity, implementing improvements to ensure accuracy and reliability.
• Mapped out ranch and land properties that match our criteria in Colorado using GIS software and linking the map to its respective dataset in Airtable.

Research Data Entry Data Cleaning Data Visualization Real Estate Airtable Excel Google Sheets MLS County Records GIS Land.id onX Map CRM Database

Jan 2022 – Dec 2023
Ontario, Canada
· Remote

Real Estate Transaction Coordinator

Keller WIlliams Edge Realty Brokerage

• Oversaw the end-to-end real estate transaction process of the brokerage with 50+ brokers, ensuring accuracy, thoroughness, and compliance with legal requirements for all paperwork and documentation using NexOne (real estate CRM).
• Supported up to 40+ transactions per month through administrative functions.
• Regularly updated and maintained communication with clients, agents, title officers, lenders, etc.
• Developed and supervised transaction timelines, ensuring timely achievement of essential milestones and proactively addressing potential issues.
• Reviewed and formulated contracts, addendums, lawyer letters, agent commissions and associated documents to ensure precision and completeness using LoneWolf.

Real Estate CRM Database Excel

Portfolio Work
Projects

SQL & Dashboard Projects

Built portfolio-ready analyses involving cleaning, exploratory analysis, database workflows, and stakeholder-friendly outputs.

SQL Power BI Excel

Featured Projects

US Household Income Exploratory Data Analysis

Explores the US Household Income dataset using MySQL to perform data cleaning, transformation, exploratory data analysis (EDA), and automation. The goal is to uncover meaningful insights about income distribution across the United States, including geographic trends and potential anomalies within the data.
GitHub Link

SQL