Hi! I'm Fierdy Pandu Setiawan, you can call me Pandu. I will guide you through my Portfolio from here.

I have an academic background and hold a Bachelor of Communication Sciences degree in Communication Sciences (Pasundan University, Bandung). Previously a Promotion/Marketing Staff in Sharp Corporation, an electronic products manufacturing company based in Japan for 1 year. My passions in technology, data, and information, and how all of those combined have become crucial in the current global trend, drive me to self-taught programming without a prior Computer related background.

With my previous background that handles communication and communicating ideas, Planning and Organizing events and promotional events to gain brand awareness, and leading teams combined with skills that I have gained such as programming and Data Analyst from various sources either by self-taught or through courses I can leverage data analytical skills to improve corporate performance.

Spreadsheet: Property-Listings-Analysis-Kuala-Lumpur
Description: The dataset contains 4832 records. There is a list of properties with location, price(in RM Malaysia), number of rooms, bathrooms, car parks, property type, size(of the entire building), furnishing types. The project includes the following steps: data loading, data cleaning and preprocessing, filling missing values, EDA (exploratory data analysis), analyzing properties based on location, measuring statistical factors, hypothesis testing.
Skills: data cleaning, data analysis, descriptive statistics, correlation, regression, hypothesis testing.
Technology: Spreadsheet.
Results: Review of the property listings in Kuala Lumpur, data-based business analysis.

Code: TheLook Query
Deck: TheLook Spreadsheet
Description: My submission for The Look Ecommerce SQL problem for Revou bootcamp
Skills: Standard Query Syntax, SQL Aggregate Functions, SQL Joins, SQL Data Type, SQL Date Format, SQL Window Function.
Queries:

• Get the number of unique users, number of orders, and total sale price status and month
• Get frequencies, average order value and total number of unique users where status is complete grouped by month
• Find user id, email, first and last name of users whose status is refunded on August 2022
• Get the top 5 least and most profitable product over all time
• Get Month to Date of total profit in each product categories of past 3 months, breakdown by month and categories
• Find monthly growth of inventory in percentage breakdown by product categories, ordered by time descendingly. Insight provided in the slides

Technology: SQL, Google BigQuery, Google Sheets, Google Slides
Results: the slide deck with SQL analysis and recommendations on how to improve the cost of production, better inventory planning and management.

Code: Mutual Fund Dataset
Deck: Mutual Fund Sheet
Description: Analyzing the current type of mutual bonds data to run a thematic communication campaign for the upcoming government bond investment product with segmenting campaign for each types of consumer.
Skills: data cleaning, data preparation, data communication, data aggregation, exploratory data analysis, cluster analysis
Technology: Python, Pandas, Numpy, Seaborn, Matplotlib.
Results: the slide deck with thematic communication campaign analysis and recommendations on how to segment different types of consumers of each type.

Code: Mutual Fund Dataset
Deck: Mutual Fund Sheet
Description: Further analyzing the previous type of mutual bonds data to better understand customer behavior so that we can make better-tailored campaigns to a few different relevant customer segments by using customer clustering methods based on transaction behavior and demographic factors.
Skills: data cleaning, data preparation, data communication, data aggregation, exploratory data analysis, cluster analysis, Regression, Regression Model, Benefit Cost Analysis
Technology: Python, Pandas, Numpy, Seaborn, Matplotlib.

Visualization - Tableau: Airbnb Singapore Vis
Visualization - Looker Data Studio: Airbnb Singapore Vis
Description: Tableau Public dashboard consisted of: Number of Listings, Number of Hosts, Number of Listings per neighborhood group and neighborhood, Top 10 Listings based on total reviews, overall average number of reviews, grouping number of listing per group based on number of listings per host.
Skills: Connect and combine/ join datasets, Data formatting, Visualization, Calculated field, Interactive Dashboard
Technology: Tableau.
Results: created an analytical dashboard to support daily activities of a company involved in apartments renting business.

Deck: COVID-19 Vaccination Deck
Dashboard: COVID-19 Vaccination Dashboard

1. Retail Store Performance Analysis