How it all started

I only wanted to learn visual basic so that I could automate those tedious, repetitive tasks. As I was watching a video tutorial by Wise Owl, the YouTube recommender algorithm did its magic and displayed someone comparing Google and IBM's data analytics programs. Then one thing lead to another, or I should say one specialization followed by another.

Learning in a new field takes a lot of passion, devotion, and discipline to keep moving and stay motivated. Understanding the fundamentals of statistics, probability, programming, and business analytics is not easy. Writing code to produce meaningful graphs is one thing; having a statistical background to analyze these graphs is another. I spend hours trying to understand what, why, and how things function. Most of the time, I'm happy with the results, but sometimes I find that the more I delve into it, the more complicated it becomes. Moving into the path of data science is daunting but is fulfilling.

It's a never-ending adventure of
building and debugging.


--- Things I do ---


Data Analysis

The goal of analysis, whether it be descriptive, diagnostic, prescriptive, or predictive, is to provide us with solutions. This section focuses on handling file formats, investigating various methodologies (such as RFM, Cohort, and Monte Carlo), and displaying results.

Text Analytics

This section is all about text analytics, especially Sentiment Analysis, Text Categorization, and Text Mining.
Text analytics can be used to uncover current trends as well as discover what our customers thought of our products and services. NLP through the internet could be used to determine the people's current conundrums. Do you recall the "piggy bank" with the goal label? By simply modifying the product's appearance, it generated significant sales from regular goods, It answer to people problem of saving money.

Machine Learning

Machine learning is a branch of artificial intelligence (AI) and computer science which focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accuracy.
Various machine learning algorithms will be used in this section depending on the project. To determine the optimum model for the problem, multiple feature engineering and feature selection methodologies will be used.

Data Visualization

Data visualization is the graphical representation of information and data. It is utilized in several stages of the data analysis pipeline.  Insights into trends, outliers, and patterns can be gained by using graphs and charts. It's also a fantastic opportunity to share what we learned about the data.

Q: How many working experience do you have as Data Analyst | Businesss Analyst | Data Science?

A: none

well...

I've been a manager for a while now, and part of my job is to find insights to help businesses make better decisions. This includes any and all available resources, such as data.

and...

Data Science is not professional programmers per se. The task is to analyzing data using specialized data science libraries. With my current proficiency, I can handle large amounts of complex data to analyze.

Wacuman Incorporated

Assistant General Manager

Acting on behalf of the executive taught me to be more precise in planning, committed to implementing the project, and accountable for the result.



Daiso

Store Manager

(ETL) Extracting data from database using JDA & SAP software. Transform - using excel to clean, sort, and filter data for sales and inventory analysis. Being responsible for overall management of the business leads me to be more creative in finding ways to increase sale and minimize lost.



Genneva Pte. Ltd

Operations Supervisor

Started out as a customer service representative and worked my way up to supervisor.
My responsibilities include ensuring timely and accurate data processing, high data integrity, and accurate inventory movement.



Jollibee Foods Corporation

Shift Manager

Working for the Philippines' largest fast food chain. I learned how to use various analytical methods to help increase our sales, improve our customer experience and loyalty programs, and reduce inventory and labor costs. Regular monitoring of store performance presents robust and actionable insights that help us make invaluable business decisions.

Projects


Data Analysis


Customer Segmentation

EDA Mobile Application

Customer Lifetime Value

Market Basket Analysis


Text Analytics


Lexicon
Sentiment Analysis

Emotional Classification

Google & Twitter
Hot Topic

News Article Topic Classification

Professional Development

In a world where technology is getting more complex and interconnected. Education has become more flexible and available, and "Massive Open Online Courses" have opened doors for professionals looking to further their education.

I took several data science specialization, statistics, watched tons of online tutorials, read documentation, and blogs and one thing will always pop up on my mind

"The more you know, the more you realize that you don't know" by Aristotle

I am still not an expert in coding, but I have learned the fundamentals and built a solid foundation in writing effective, functional, and reusable code. I can comprehend complex syntax, which helps me collect bits and bytes of code to solve the problem at hand.


Specialization


IBM Data Science

IBM Machine Learning

Google Data Analytics

Python for Everybody

Postgresql Everybody

Python 3

Data Viz w/ Tableau

Excel Skill for Business

Business Analystics

Effective Communication

Relevant Courses


Name Issuing Organization
Google Analytic for Beginners Google Analytic Academy [...]
Excel Power Tools for Data Analysis Coursera: Macquarie University[...]
Data Analysis with Excel Pivot Tables 365Data Science[...]
Advanced Microsoft Excel 365Data Science[...]
The Structured Query Language (SQL) Coursera: University of Colorado Boulder[...]
Data Wrangling, Analysis and AB Testing with SQL Coursera: University of California, Davis[...]
SQL 365Data Science[...]