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Financial Benchmarking and Insights Tool

CFR File Generation

Consistent Financial Reporting (CFR) is one of the four financial data used in the Financial Benchmarking and Insights Tool (FBIT) service. The CFR data is typically received yearly by mid/late August when Local Authorities require maintained schools to complete their financial returns. This financial data is processed along with a few dimensional data (non-financial data) to generate the School Financial Benchmark (SFB) dataset named maintained_schools_master_list and an accompanying transparency file. See FBIT Domain for more information on FBIT Financial data.

This documentation outlines input data, quality assurance, data sourcing, cleansing and transformation procedures required to generate downstream datasets for deployment in the FBIT data pipelines.

Note: Automated Generation (2024-2025 Onwards)
Starting from the 2024-2025 academic year, the generation of the maintained_schools_master_list.csv and transparency files is fully automated within the core FBIT Python data pipeline. The pipeline automatically reads the raw CFR_YY-YY_Data.csv and ancillary datasets (GIAS, Census, SEN, etc.) from Azure Blob Storage and performs all necessary mapping, federation aggregations, and DNS masking natively.The SQL-based manual generation steps (steps 1 through 5) documented below are now considered legacy and are only required for processing or regenerating historical CFR data prior to the 2024-2025 academic year.

Prerequisite (Legacy SQL Process)

  1. Read and write access to DfE Financial Benchmark Sharepoint.

  2. Read and write access to Azure blob storage within DfE Platform Identity directory.

  3. In Azure blob storage, ensure a folder with the naming convention 20YY exists in the default folder that represents the end of the reporting academic year. For instance, 2025 for the 2024-2025 academic year. This folder must contain the raw CFR_YY-YY_Data.csv and all ancillary .csv dimension files.

  4. Access to DfE iStore, the server where all COLLECT data is stored).

  5. For historical processing only: Create a folder with the naming convention yy-yy in CFR Data Procurement Process Sharepoint location that represent the reporting academic year. For instance, 24-25 for 2024-2025 academic year.

  6. For historical processing only: Copy the five (5) .sql files over from the previous academic reporting year’s folder to newly created academic reporting year’s folder. The files are;

    • My_Step1.sql
    • My_Step2.sql
    • My_Step3.sql
    • My_Step4.sql
    • My_Step5.sql

  7. For historical processing only: Create a local Database to be named CFRyy where yy represents the end of the reporting academic year.