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Brillian DMA Introduction
A structured, guided learning path to Data Management and Analytics
Setting up
The first step to becoming a brilliant data professional is your tooling and environment setup.
Programming Environment
Get your programming environment set up with the right tools, i.e Python, Git, a code editor, and Python data analysis libraries.
R and Python Programming Starter
A 2-hour guide for absolute beginners that are new to programming. Created by the team at Algoritma as a gentle introduction to R and Python
Learning Path
| i | Date | Topic | Description |
|---|---|---|---|
| 1 | 16 Aug | Set Up and Tooling | Get your programming environment set up |
| 2 | 19 Aug | Overview: Enterprise Data Management | An overview of enterprise data management and its historical context |
| 3 | 20 Aug | Modern Enterprise Data Management | An overview of the key components of enterprise data management |
| 4 | 21 Aug | Python Programming Basics | Python 101 |
| 5 | 22 Aug | API Programming with Python | Everything to get you started with creating programs using Financial APIs |
| 6 | 23 Aug | Data Analysis with Pandas I | The de-facto library for data manipulation and analysis in Python |
| 7 | 26 Aug | Data Analysis with Pandas II | Graded Quiz |
| 8 | 27 Aug | Lab: Data Manipulation | Using Pandas, perform a series of data manipulation and analysis tasks on Indonesia banking sector data provided by Sectors |
| 9 | 28 Aug | Recap and Practice | Time for a recap of the lessons thus far! |
| 10 | 29 Aug | Introduction to RDBMs and ERD | DuckDB, Relational Database Management Systems, creating SQL from existing CSVs |
| 11 | 30 Aug | Lab: SQL Practice | SQL Queries in Practice |
| 12 | 2 Sep | Data Visualization Basics | An overview of data visualization history and why it is important in the big data era |
| Data Visualization Fundamental | An overview of the data visualization fundamental | ||
| 13 | 3 Sep | Data Visualization Tools | A summary of widely-used data visualization tools (+ hands-on into Tableau Public) |
| Lab: Data Visualization | Practical graded exercise for data visualization and data storytelling | ||
| 14 | 4 Sep | Lab: Data Visualization | Practical graded exercise for data visualization and data storytelling |
| 15 | 5 Sep | Introduction to NoSQL | Basic understanding on NoSQL paradigm and its examples, PostgreSQL, and Redis for caching |
| 16 | 6 Sep | Lab (cont.): Redis for caching; Introduction to Apache Kafka | Learning fundamental key concepts on Apache Kafka |
| 17 | 9 Sep | Lab: Data Streaming | Orchestrating a simple data streaming pipeline using Apache Kafka, Spark, Cassandra, MySQL, and Streamlit (optional) |
| 18 | 10 Sep | Lab (cont.) + Final Project | Orchestrating a simple data streaming pipeline using Apache Kafka, Spark, Cassandra, MySQL, and Streamlit (optional) |
| 19 | 11 Sep | Final Project | Work on the final project for the Brillian DMA course |
| 20 | 12 Sep | Final Project | Work on the final project for the Brillian DMA course |
| 21 | 13 Sep | Final Project | Work on the final project for the Brillian DMA course |
Helpful Resources
Beyond Brillian DMA (this app you’re looking at), there are a number of resources you can use to supplement your learning.