Implementing SFA4HANA, EDS, and SAP4HANA for GT Sales at the PT. Pinus Merah Abadi site, a subsidiary company distributing KSNI products across Indonesia. This involves preparations for go-live, including creating Sales user data, cleansing and migrating Customer data and Warehouse Stock data for go-live readiness.

• Handled more than 200.000 dummy data based on real world's complexity in quick commerce industry using SQL BigQuery with average score 2.9 of 3 • Make 3 KPI Dashboards (Gold, Silver, and Bronze) and annual end to end company performance • Created customer segmentation profiling using K-Means Approach and analyzed cluster behave in app funnel to improve marketing performance and increase transactions by 20% • Created impact analysis to identify performance based on recommendations • Analyze the three customer categories to increase sales for the next year.Present and received satisfactory results and feedback from Telkom Analytics Team as a reviewer.

Executed comprehensive testing on the Learning Management School Application across Web, Android, and iOS platforms in Staging, UAT, and Production environments. Additionally, developed a test result module to optimize reporting efficiency.

a. analysis ACE Hardware data sales• Data cleaning & preparation using Python. • EDA using Google Sheet • Predictive Analysis using random forest in Python • Visualized players performance with Tableau b. Understanding business problem/issues • Defined business problem & root cause analysis from the business problem • Communicated the business problem, created hypothesis and test hypothesis • Proposed Solution using metrics recommendation c. Data Exploration from The Look E-commerce dataset using Google BigQuery • Define and monitor key metrics • Used basic SQL & aggregate functions • Data cleaning & formatting in SQL (SQL date format) • Used SQL joins, union, CTE & window function d. Data cleaning and preparation, EDA, correlation, cluster analysis, and cluster interpretation of mutual fund investment data using Python • Defining business problems and business recommendations • Data cleaning and preparation • EDA, clear visualizations, cluster analysis and interpretation to guide decision-making e. EDA and create clear visualization with an interactive dashboard using ACE Hardware sale data with Lookers (Google Data Studio) and Tableau • Used Tableau basic and functionalities (Connect and Combine) and setup filtering • Created hierarchies, used calculated fields and visualized exploratory data analysis in Tableau • Created charts and calculations in Lookers (Google Data Studio) • Designed an interactive dashboard in Tableau and Lookers (Google Data Studio)

Conducted annual testing on 10 applications within BNI International Treasury Finance, delivered User Acceptance Training (UAT), and implemented a test result module to streamline reporting processes.

Instructed Bank Indonesia employees on the Core Banking System module, addressed and resolved branch issues analyze processed data to determine the next steps in business processes and actively support them. Conduct User Acceptance Testing (UAT) using predefined scenarios and efficiently manage and resolve user issues.

Instructed Sales and Admin teams on utilizing the Sales Force Automation Tab and Web DMS 3.0. Offered support for distribution issues within the Kino System and effectively executed data migration for distributors. Clean and analyze stock data to plan for next month's inventory and maximize profit. Achievement: Appointed as Cluster Lead for the Solo region in Java. Led a project to handle field issues locally, ensuring only technical issues are escalated to the central team, reducing their workload.

Managed the migration of data to a new Web Support application, conducted training sessions for Honda employees on the neuromotor e-business application module, and adeptly addressed user input, complaints, and problems, resulting in enhanced client satisfaction. Analyze service and spare parts sales data to decide on future sales promotions.

Surveyed villagers, quantified land ownership areas through accurate measurements, and generated land certificates to establish a thorough and well-organized record. Collect data, clean it, and group it by the applicant's location to process it more efficiently.