July 2026 performance summary for DUNE/duneana. The primary focus this month was a strategic refactor of RawDigitAna to enable per-entry processing and improve memory management, setting the stage for scalable analytics on large datasets. Key architectural changes replaced fixed-size arrays with dynamic vectors and removed hardcoded channel and tick limits, addressing scalability bottlenecks and reducing memory pressure. While no discrete bug fixes are recorded in this dataset, the refactor directly mitigates memory-related issues and improves robustness when processing increasing data volumes. Code changes are anchored by the commit that formalizes the analysis module refactor, supporting easier future maintenance and extension of the analytics pipeline. This work strengthens the team's ability to deliver faster insights with lower resource usage, directly contributing to improved throughput and scalability for DUNE/duneana.