Trading Data Analytics Demystified — Your Complete Toolkit

In this new part of series we’ll explore various techniques and tools to analyze financial data. This series aims to provide insights into understanding market trends, patterns, and making informed decisions.

First, we’ll begin by setting up your trading data analysis environment with some introductory articles, followed by more targeted financial analysis.

• Part 0: Uploading parquet files to MinIO S3 . You’ll be able to upload with Pyspark the generated parquet files into MinIO. This will be the main serving way we’ll use to analyse aggregated data or identify trading opportunities.
• Part 1: First steps with DuckDB and Parquet Files. We’ll use in several articles DuckDB as the analytical execution engine. In this article we’ll see how to create a DuckDB table in memory based on parquet files from MinIO.
• Part 2: Top momentum using DuckDB and Polars. In this article, we will demonstrate how to identify the top momentum stocks by analyzing log returns, leveraging the capabilities of Polars.
• Part 3: Crafting analytics charts with Superset. In this new part of series we’ll explore the process of visualizing our earlier analysis through a dashboard, leveraging Apache Superset.