Ee Ann Ng
Verified Expert in Engineering
Business Analysis Developer
Ee is an of the box thinker with a passion for learning, problem-solving, and overcoming challenges. A good bridge between business and technical teams, she has a solid business acumen, data literacy, and technical skills. Ee has the ability to grasp business processes and operations through exploring and analyzing data in natural sources or warehouses. She is always detail-oriented and a strong advocate of data validation. Quality assurance (QA) checks are always a given.
Qlik Sense, Microsoft Power BI, ThoughtSpot, Python, Databricks, Amazon SageMaker, SQL, Snowflake, Data Manipulation, Data Visualization
The most amazing...
...process I’ve used is to understand stakeholder KPIs and goals from their perspective and deliver intuitive solutions that accurately address their needs.
Lead Data Analyst
- Maintained data tables in Snowflake and prepared a Snowflake schema data model on the ThoughtSpot platform. Trained users for self-service analytics on ThoughtSpot for simple data extraction and analysis and delivered the more complex pinboards.
- Developed a ThoughtSpot data model evaluation tool that flags out inefficiencies in the data model, allowing fine-tuning of existing data models to remove redundancies and increase usability.
- Developed an automated data dictionary creation tool that provides sample values for measures, attributes, and formulas to help ease user onboarding onto ThoughtSpot.
PowerBI Developer | Castings Manufacturing Company
Bingham and Taylor Corp.
- Developed a dashboard for top management with a birds-eye view of the business performance and trend over time in orders, sales, shipments, production, costs and operating income, inventory, etc.
- Consolidated all relevant attributes and measures into a Snowflake schema data model, creating a single source of truth across the business.
- Conducted full data validation and testing against existing reports to ensure all numbers were accurate and provided documentation for future code maintenance.
Business Intelligence (BI) Project Lead
- Developed a regional sales dashboard that is fully dynamic to allow visibility on every level of every hierarchy for sales teams to answer questions regarding sales performance within their designated team, territory, product, and customer accounts.
- Created all relevant dashboard levels of hierarchies for every entity, example product hierarchy, customer/account hierarchy, sales team hierarchy, and territory hierarchy. Allowed filtering and drilldown on every single level of every hierarchy.
- Utilized the synergies of multiple cloud technologies like Amazon SageMaker for ETL, Redshift for data storage, and Qlik Sense for the BI dashboard. Allowed for high-speed dashboard response time and rapid data refresh times.
- Provided a data quality page to indicate percentage and reliability of KPI numbers, with an exact breakdown of missing/incorrect data points and proposed resolution. Allowed upstream bugs in the data pipeline to be identified and corrected.
- Took care of end-to-end design, implemented, tested (system integration testing (SIT) and user acceptance testing (UAT), including test case creation and user training), and finally deployment to production.
- Used market basket methodologies and insights from data. Provided recommendations to a finance and business franchise on product bundles and promotional items to increase average ticket size of customer purchases and drive up sales.
- Provided consultation to businesses on campaigns with tests versus control groups, then evaluated impact to inform decisions on finetuning future campaigns, optimizing campaign drivers and targetting high return on investment (ROI) customers.
- Performed forecasting of bank portfolio product profitability. Based on projected product profitability, provided advice on campaign activities to increase profitability and for account and customer segment targetting.
- Provided training to client users on utilizing a proprietary BI tool to harness insights from data and assisted comparison of client-specific KPIs versus industry benchmarks. Oversaw the ingestion of data, ETL, and loading of features into a tool.
- Worked with regional sales and marketing stakeholders to understand business goals and KPIs. Worked with engineers to ingest data from IT source systems into data lakes, and delivered automated dashboards to allow business users to monitor KPIs.
- Worked with the data engineering team to explore regional level data across IT source systems. Created a unified data model within a data warehouse, enabling a single source of standardized data for usage across the region.
- Performed market segmentation and leads scoring using cluster analysis (unsupervised machine learning (ML)). Segmented customers by demographics, rank tier customers for targeted marketing efforts on most valuable customers in each segment.
- Harmonized data from various source systems to create a regional sales funnel dashboard, allowing businesses to monitor the performance of different sales stages in the funnel at the regional and market-level to make strategic and sales planning.
- Built data quality dashboards to monitor daily data loads, alerting data engineering team of failures. Provided confidence levels for data analytics products.
- Automated reporting workflows for less digitized departments by creating pipelines that transformed their document data and loaded them into databases and then replaced manual reports with visual dashboards.
- Created a tool to minimize datasets in Microsoft Power BI files, allowing 10 times faster-loading speed and response time of Microsoft Power BI dashboards, improving usability and maintainability.
- Developed a train and driver scheduling algorithm. Used a resource-constrained shortest path program of graph network theories. Optimized the schedules to ensure cost-effectiveness and labor law adherence while covering necessary routes.
- Ensured that trains do not exceed maintenance mileage and return to the depot for routine maintenance. Ensured that drivers get sufficient break time between blocks of consecutive working hours while minimizing out of home shifts.
- Developed an algorithm to schedule cargo shipments around the globe from port to port, minimizing travel distance while covering all shipments before their due dates. Optimized the plan that saved the shipping company millions of dollars monthly.
- Created an algorithm to schedule the sequence of metals to be produced in the production lines in a metal factory, to minimize scrap and machine setup times.
- Developed business essential supply chain planning applications using the proprietary Quintiq platform. Applied object-oriented modeling concepts and best practices.
- Involved in the full software development life cycle, understanding business problems. Translated to a software solution, to front-end UI design and back-end implementation, to testing, bug fixing, and supporting UAT before Go-live.
- Created applications that brought high value to businesses through seamless user adoption across industries. Used by airport ground staff scheduling, kitchen meal prep scheduling, train scheduling, and manufacturing workflow scheduling applications.
Stakeholder Mapping Tool
Robotic Process Automation Tool
The tool consumes this file and has a start and stop functionality with a progress bar to track completion status. The device comes with fail-safe recovery features to account for connectivity drops, accidental run interruption, etc. It can pick up and continue the run from any point with very stable performance.
After I completed the automation run, the tool also exports and compiles the run results into a single comprehensive Excel report with a summary page and statistics charts. The tool was fully developed three weekends and distributed as an executable file to other consultants across the region, which works out of the box. It was a phenomenon within the consulting department as it improved the productivity of every consultant by hundreds of hours, allowing a short turnaround time for clients to generate forecasting reports. Such RPA tools usually take a full team of business/system analysts, engineers, and testers to design, implement and test.
Set up Microsoft for a Non-profit Organization
APAC Electric Vehicle Readiness Analysishttps://github.com/enAnne/WorkSamples
The data is scraped using Python, Selenium, and API requests from various online sources: ChargeMaps, HERE, anywhere (Thailand), EVStation (Malaysia), Naver (Korea), NewMotion, NZ Transport Agency (New Zealand), Open Charge Map, OpenStreetMap, PlugShare, and PlugSurfing, among others.
The data collected are charging station locations and the connectors available in each area in JSON format, then flattened into tables and cleansed and standardized across all data sources.
The complexities faced in this project are data availability, data duplicity, and data quality. When the same point of interest (POI) exists in different sources, they vary slightly in naming, coordinates, connector counts, etc., posing a challenge to identify the most accurate source of truth for the unique POI record. This has been addressed in innovative ways to develop a comprehensive dashboard.
Python, SQL, Snowflake, Scala
Qlik Sense, Microsoft Power BI, Microsoft Excel, Amazon SageMaker, Plotly, CPLEX
Business Intelligence (BI), Linear Programming, Object-oriented Programming (OOP)
Google Cloud Platform (GCP), Azure, Databricks, Amazon Web Services (AWS), Dataiku, Microsoft, Oracle
Databases, Microsoft SQL Server, Redshift, Amazon S3 (AWS S3), SQL Server Integration Services (SSIS), SQL Server Analysis Services (SSAS)
ThoughtSpot, Business Analysis, CSV, Data Manipulation, APIs, Google BigQuery, DAX, Data Engineering, Data Analysis, Reporting, BI Reports, Data Visualization, Data Analytics, Machine Learning, Robotic Process Automation (RPA), Web Scraping, Optimization, OR-Tools, Delta Lake, ERD, Data Cleansing, Critical Thinking
Bachelor's Degree in Mechatronics Engineering
Monash University - Subang Jaya, Malaysia/Clayton, Canada
Microsoft Certified: Azure Fundamentals
Data Analyst with Python
Data Driven Decision Making
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