About me

Validated by DataCamp through a series of timed technical exams and a real-world practical case study. Demonstrated proficiency in using SQL for complex data management, performing exploratory data analysis (EDA), and applying statistical concepts to drive business decisions.

Validated by DataCamp through a rigorous technical exam and a practical business case study. Proficient in end-to-end database workflows, including complex data extraction, joining, and aggregation. Specialized in cleaning and validating raw datasets to ensure data integrity for business reporting and metric calculation.

In this learning journey, I explored intermediate and advanced SQL concepts, primarily using PostgreSQL. I learned how to logically design databases using normalization and dimensional modeling. I mastered complex querying techniques, including advanced joins, set operations, and various subqueries like CTEs. I also gained skills in data manipulation using CASE statements, date/string functions, and arrays. Finally, I learned to write powerful window functions for analytics and manage database views and roles.

This program included over 200 hours of instruction and hundreds of practice-based assessments, which helped me simulate real-world advanced data analytics scenarios that are critical for success in the workplace. The content was highly interactive and exclusively developed by Google employees with decades of experience in advanced data analytics and data science. Through a mix of videos, assessments, and hands-on labs, I was introduced to advanced data analytics tools and platforms and key technical skills required for an advanced role.

This program was uniquely mapped to key job skills required in a Power BI data analyst role. In each course, I consolidated what I learned by completing a project that simulated a real-world data analysis scenario using Power BI. I also completed a final capstone project where I showcased all my new Power BI data analytical skills by connecting to data sources to transform data into an optimized data model and demonstrating data storytelling through dashboards, reports and charts to solve business challenges and identify new opportunities.

I gained hands-on expertise in the full data analysis lifecycle, from wrangling datasets with SQL and Python to visualizing insights in Excel and Cognos. My projects included analyzing vehicle inventory with pivot tables, creating interactive KPI dashboards, and extracting financial data with Pandas. I also built regression models to predict housing prices and developed a dynamic Python dashboard for flight reliability, effectively bridging technical rigor with data storytelling.

Completed a Full Learning Path with Professional Skill during 59 hours in Microsoft Excel. This comprehensive program covers Excel from basic to advanced levels, including data manipulation, forecasting, regression, and statistical analysis. Gained hands-on experience with data cleansing, visualization, pivot tables, Power Pivot, VBA macros, and advanced analytical techniques.

My engineering training provided a rigorous quantitative foundation, emphasizing spatial logic, complex system modeling, and statistical risk assessment. This background honed my ability to decompose ambiguous real-world problems into structured data models, directly translating geological field methodologies into modern data-driven decision-making frameworks.

Engineered a dual-phase SQL analytics pipeline to bridge B2B merchant acquisition inefficiencies with B2C customer retention leaks, directly optimizing marketing capital allocation and product lifecycle strategy. By offloading complex window functions to the database tier, I delivered a lag-free executive dashboard that identified high-yield traffic sources and quantified critical churn risks.

Led the end-to-end data analytics lifecycle for Salifort Motors to diagnose a critical 23.8% employee turnover crisis by developing a predictive Random Forest model that achieved 99% accuracy and identified key drivers like satisfaction and workload. Translated complex technical findings into actionable strategic recommendations, directly enabling leadership to implement targeted retention interventions in high-risk departments.

Addressing a critical class imbalance in a 466k-row lending dataset, I engineered a leakage-free pipeline and deployed a Balanced Logistic Regression model to proactively identify high-risk borrowers. This end-to-end solution transformed raw data into actionable business intelligence, directly enabling stakeholders to mitigate potential financial losses through data-driven approval strategies.

Acting as a BI Analyst for PT Sejahtera Bersama, I engineered an end-to-end data pipeline in Google BigQuery to resolve fragmented sales data, enabling the identification of a critical "Volume vs. Value" paradox between high-frequency eBooks and high-revenue Robots. By visualizing these insights in Looker Studio, I formulated three strategic initiatives (including product bundling and regional replication) projected to unlock over IDR 175M in optimized revenue.

Architected an end-to-end analytics solution for Indonesia's largest pharmaceutical retailer by engineering a BigQuery ELT pipeline to unify 672K+ transactions and implementing complex tiered margin logic to resolve data silos. This initiative enabled real-time performance monitoring that identified a critical 30% geographic revenue dependency and pinpointed specific operational bottlenecks causing a 0.4-point customer satisfaction gap in key branches.

This project-based internship focuses on the core concept of the end-to-end data science lifecycle, ranging from initial business understanding and data collection to automated model deployment. Participants leverage a technology stack including Python, R, and SQL to master specific skills in exploratory data analysis, feature engineering, machine learning modeling, and version control with Git.

This project-based internship provides Business Intelligence training focusing on technology stacks like SQL (PostgreSQL and BigQuery), Microsoft Excel, and Looker Studio. It cultivates specific skills in database management, advanced data manipulation (such as CTEs and joins), and data storytelling through interactive dashboards for banking portfolio analysis.

This project-based internship provides hands-on experience in SQL querying, Google BigQuery data warehousing, and Looker Studio visualization to support analytical business needs. Participants acquire specific skills in ETL pipeline design, exploratory statistical analysis, and data storytelling to transform complex big data into actionable insights.

Managed end-to-end operational logistics for private clients, ensuring seamless execution of daily schedules across diverse geographic regions. Operated as the primary point of contact for time-sensitive travel requirements, leveraging real-time data analysis to optimize routes and mitigate delays.