endpoints – tested the security to ensure it is robust. Moved data from on premises to LiquidLogic database and LiquidLogic file store storage containers in the resource. August 2023: Uploaded data into storage, indexed the data, built an indexer, built skillsets. Proved the ability to search unstructured data using Apache Lucene query language in a web application leveraging the index processes created. September 2023: Produced ‘knowledge store’ output into Azure table storage to feed organisational reporting tools (this was later replaced by creating a new database structure for reporting and using these tables as the knowledge store). Created a reporting product based on the information held in the knowledge store. Developed a Power BI dashboard connected to the knowledge store, identified and implemented suitable ‘network’ visuals to produce ecomaps. Nov/Dec 2023: Demonstrated the prototype of the product and gathered feedback from service users, this was through presentations at several conference style meetings to hundreds of social workers. December 2023: Review of work to date, project team encouraged by feedback and evidence of positive engagement from service users. Consolidated position and identified key next steps. January/February 2024: New Data Factory infrastructure implemented, making the solution more cost effective and laying foundations for incremental loads. See Figure 4: Technical Architecture Diagram below. February 2024: Development of new Power BI dashboard based on user feedback of prototype. This was linked to tables views created by the Data Factory pipelines, using direct query methods to avoid large data loads and increase data retrieval performance. March 2024: Incremental load/data refresh and LiquidLogic forms work being undertaken. Cons