Data Warehouse for Algorithmic Trading Stocks-Price Forecasting on Digital Research Infrastructure using Machine Learning Modelling
Time & Date: 9:00am – 10:00am , Wednesday, April 21, 2026
Location: Room HS107 and via Zoom (see email and registration information), Computer Science Department, Okanagan College
Registration is open now: https://events.vtools.ieee.org/m/555684
Join this presentation to explore how a Data Warehouse system is built to manage and process large-scale stock market data. The project demonstrates how raw financial data is transformed into structured formats that can be efficiently queried and used for predictive modelling.
You’ll learn:
- How Data Warehouses store and organize large datasets
- Star schema design in a real system
- How data pipelines automate transformation of financial data
- How machine learning models use prepared datasets for predictions
- How large datasets are processed efficiently
Abstract:
This presentation explains how large volumes of stock market data are organized and processed using a structured database system. The system takes raw financial data and converts it into a format that is easier to store, search, and analyze.
The data is processed through an automated pipeline that calculates key financial values such as price changes and trading volume summaries. The structured data is then stored in an optimized system that allows fast access and efficient analysis.
This approach helps make large financial datasets more usable and easier to work with.
Speakers Bio:
Emilio Iturbide Gonzalez is a graduating Computer Science student at Okanagan College with interests in data systems, software engineering, and artificial intelligence.
He has worked on building a Data Warehouse system designed to manage and process large volumes of stock market data. His work focuses on creating efficient data pipelines, organizing complex datasets, and supporting data-driven applications.
He is interested in building practical systems that connect software engineering, data processing, and real-world applications in technology.
For further information please contact: Youry Khmelevsky (email: Youry at IEEE.org)
Refreshments will be provided