Bring AI into everyday development and analysis.
I explore AI for requirements, implementation support, code reviews and data analysis, checking evidence and actual behavior to find useful applications in business.
Software Development Engineer & BI Analyst
From business systems to analytics and cloud operations.<br>Connecting technology and business to build solutions people can keep using.
Explore my work ↗GitHub ↗Scroll to explore the connections between AI, data and the cloud.
My work focuses on Tableau reporting, CRM Analytics datasets and SAQL, and Salesforce Apex, LWC and Flow. Do dashboard numbers agree with their sources? Does RLS limit each user's data correctly? Do business processes and external integrations work together as intended? I verify the visible results alongside the data, permissions and logic behind them.
Connecting AI-assisted development, data analysis and business applications.
02 / DATAFrom metric definitions and data models to dashboard design and validation.
03 / APPLICATIONLWC, Apex, Flow, API integration and approaches to quality assurance.
04 / OPERATIONSCloud environments, monitoring, incident response and recovery preparation.
I explore AI for requirements, implementation support, code reviews and data analysis, checking evidence and actual behavior to find useful applications in business.
A sales analytics solution connecting Azure SQL to Tableau Cloud, covering dashboards, row-level security and extract performance improvements.
Clarify grain, date ranges and comparison conditions, then organize analytical data using SQL or SAQL.
Connect broad trends to detailed exploration with consistent filtering, drill-down and units that support real decisions.
Check metrics, views under different permissions, data freshness and page loading behavior.
Implement business logic, external API integration and approval automation with Apex and Flow, including permission design and asynchronous processing.
Connect LWC interfaces with Apex and Flow, mapping the complete journey from data entry to approval.
Include API field mappings, failure logs and retry procedures in the integration design.
Beyond the happy path, check insufficient permissions, missing input and bulk record processing.
Deploy and operate applications with Azure, Debian and Docker, manage multiple NocoBase environments, and configure monitoring, backups and Cloudflare Tunnel connectivity.
Track CPU, memory, disk usage, service health and logs, incorporating detection, notifications and investigation into operations design.
Distinguish applications, data and connection paths so the components and their dependencies are clear.
Treat log checks, backups and configuration change records as essential parts of ongoing operations.
Check connectivity, persistence and recovery procedures as well as startup status.
Salesforce · Apex · LWC · Flow · REST API
Tableau · CRM Analytics · Snowflake · SAQL · SQL · PostgreSQL
Azure / Azure SQL · AWS S3 · Docker · Debian · Git
When a dashboard lacks a necessary field, revisit business input and the data model. When data is invisible, check filters, permissions and refresh status. When an application is unavailable, follow its connections, logs and storage. I focus on how these parts shape the result rather than treating every issue as a problem with a single tool.
Align definitions, scope and periods so every displayed value can be traced.
Record differences and checks, validating both the new results and existing behavior.
Document structure, procedures and open issues so maintenance and improvement can continue.
Connect business, data and operations into one workflow.
Map business processes and data flows to identify users, situations and the problem that actually needs solving.
Connect the interface, business logic and data. Test ideas with working results and use feedback to guide the next improvement.
Include testing, permissions, monitoring and maintenance in the design so the solution remains useful in daily work.
Choose a theme to explore a path from problem to implementation. These conceptual diagrams illustrate the approach.
Map input, approval, notifications and external integrations. Begin automation where repetitive manual work is concentrated.
Align metric definitions and data grain, then design an analytical experience that moves from overview to detail.
Organize environment isolation, logs and backups to give daily checks and recovery a clear foundation.
In an Azure SQL to Tableau Cloud project, I worked on RLS, LOD expressions and extract performance, validating metrics and access boundaries.
Explore analytics practice ↗Designed Flow and Slack notification integration around Salesforce approval and rejection events, focusing on asynchronous execution and duplicate prevention.
Explore development practice ↗Worked on monitoring, backups, log management and troubleshooting in Azure Linux and Docker environments.
Explore operations practice ↗Salesforce business applications, Tableau and CRM Analytics, and cloud application operations, including data integration across these areas.
I explore AI as support for research, implementation and validation, checking generated content against real requirements and execution results.
You can find public code and activity on GitHub. Follow the link below to visit my profile.