Azure and Databricks Data Substrate for Planning

A major global manufacturer of professional-grade power tools and accessories engaged Taller in 2021 to support its connected-products software and data platform. The engagement spanned four workstreams: ERP integration and migration, an Azure and Databricks data platform, the React and AWS Serverless diagnostics team, and EDI managed services.

The client adopted a third-party AI demand-planning platform (Atlas) that delivered a 20% improvement in forecast accuracy in its first year. Atlas unified the company’s demand and supply data into a single model and drove an organizational redesign that merged demand and supply planning into one role. But a planning platform is only as accurate as the enterprise data feeding it, and getting that data right takes sustained engineering across the data warehouse, the data lake, the analytical models, and the business-intelligence layer that turns planning output into action.

Taller began building a modern Azure and Databricks data-platform team for the client in 2024, and it expanded steadily through 2026 into a multi-discipline pod: senior and principal data engineering, data-platform administration (using Terraform and infrastructure-as-code, which define and deploy infrastructure through version-controlled files, plus automated deployment), data-operations support, and business-intelligence engineering (Power BI models built on Oracle Cloud). The pod architected, built, and operated the core of the client’s enterprise data platform: a modern data-lake foundation (Delta Lake), a metadata-driven design discipline, real-time streaming architectures (Kafka, Event Hubs, Kinesis, and Spark Structured Streaming), data governance (Unity Catalog), and workflow orchestration (Databricks Jobs and Workflows). The platform ingested, transformed, and curated data from APIs, databases, files, and event streams across the client’s operational systems. Taller did not operate the Atlas planning platform itself; that was configured and run by the client’s internal planning organization. Taller operated the data foundation that flowed into Atlas from the Oracle ERP and supply-chain cloud, Dynamics, and the broader operational systems.