AcademyAcademyUsing AI and automation without the hype.
Alteryx Designer has four distinct areas and learning what each one does is the fastest way to go from zero to a working finance workflow. This post covers the canvas, configuration panel, results window, and toolbar with a concrete reconciliation example.
Matplotlib, Seaborn, and Plotly each suit a different moment in the treasury and risk workflow. This post shows you which to reach for using worked examples including yield curves, HQLA correlation heatmaps, and cash flow waterfalls.
AI coding agents can compress delivery time for treasury and risk teams in ways that are genuinely worth capturing. This post sets out where the gains concentrate, where the risks are sharpest, and how to run a review process that keeps both in check.
Alteryx Designer is a visual workflow tool that turns repetitive data preparation into a repeatable, auditable process without requiring code. This guide explains what it does, how it compares to Excel, SQL, and Python, and whether it is worth learning for Finance and treasury teams.
Snowflake and Databricks both serve financial services data teams but they are built for different jobs. This structured comparison scores both platforms across 15 weighted categories to help you make a defensible choice for your organisation.
A direct, weighted comparison of Tableau and Qlik Sense for finance and analytics teams in 2026, covering architecture, AI, governance, cost, and implementation realities. Vendor marketing will not give you this; a practitioner will.
Alteryx and KNIME are the two platforms that keep coming up in enterprise analytics procurement conversations. This structured comparison cuts through the vendor material so you can make the call based on what your team actually needs.