How Bread Standardized on the Lakehouse With Databricks & Delta Lake
This is a collaborative post from Bread Finance and Databricks. We thank co-author Christina Taylor, Senior Data Engineer–Bread Finance, for her contribution. Bread,…
AML Solutions at Scale Using Databricks Lakehouse Platform
Anti-Money Laundering (AML) compliance has been undoubtedly one of the top agenda items for regulators providing oversight of financial institutions across the globe.…
Strategies for Modernizing Investment Data Platforms
The appetite for investment was at a historic high in 2020 for both individual and institutional investors. One study showed that “retail traders…
Combining Rules-based and AI Models to Combat Financial Fraud
The financial services industry (FSI) is rushing towards transformational change, delivering transactional features and facilitating payments through new digital channels to remain competitive.…
How to Extract Market Drivers at Scale Using Alternative Data
Watch the on-demand webinar Alternative Data Analytics with Python for a demonstration of the solution discussed in this blog and/or download the following…
Scaling Financial Time Series Analysis Beyond PCs and Pandas: On-Demand Webinar, Slides and FAQ Now Available!
On Oct 9th, 2019, we hosted a live webinar —Scaling Financial Time Series Analysis Beyond PCs and Pandas — with Junta Nakai, Industry…
Democratizing Financial Time Series Analysis with Databricks
Introduction The role of data scientists, data engineers, and analysts at financial institutions includes (but is not limited to) protecting hundreds of billions…
Understanding Dynamic Time Warping
This blog is part 1 of our two-part series Using Dynamic Time Warping and MLflow to Detect Sales Trends. To go to part…
Using Dynamic Time Warping and MLflow to Detect Sales Trends
This blog is part 2 of our two-part series Using Dynamic Time Warping and MLflow to Detect Sales Trends. The phrase “dynamic time…
