DATA & AI
Data Analytics
Bridging the gap between development & analytics
Traditionally, analytics teams transformed data into centralized dashboards, but as data sources and business questions grow, this strains resources. Modern decision-makers must efficiently merge and analyze data from diverse systems to uncover insights and guide business strategies. A shared ownership approach integrates development and analytics early in projects to ensure data is analyzable from the start. We transform data challenges into business assets, helping organizations stay competitive.
Source Allies Data Engineers are about data quality, accurate insights, data-driven decisions, and providing expert level knowledge when it comes to data engineering and data science practices.
Our Work
Building a Scalable Data Analytics Platform
A global agricultural services company needed a secure, consistent way to bring data from multiple products together for analytics and other downstream...
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Structured AI Retrieval for Complex Regulations
A leading crop insurance provider needed a faster, more consistent way for underwriters to navigate a large and continually changing body of...
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Scaling Enterprise Authorization
A global manufacturing organization needed a faster, more scalable way for internal applications to evaluate organization-level permissions, feature toggles, and licensing....
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The Iterative Migration
How an iterative migration system unlocked our team to deliver a NoSQL to SQL migration....
Agentic AI Analytics: How to use an LLM to make sense of your data
In this post we combine the learnings of two previous Technically Speaking videos in order to build an AI driven analytics chatbot...
Introducing Glue Biscuit: A reference guide and library for building production quality AWS Glue jobs
Introducing a reference guide and library for working with AWS Glue....