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Data Management Solutions: Sainsbury’s Data Transformation with Snowflake

Project Summary

Solutions Adopted

  • Snowflake Data Cloud as the central data platform
  • Fivetran and Matillion for data integration and ETL processes
  • dbt (data build tool) for data transformation and modelling
  • Databricks for advanced analytics and machine learning workloads
  • Alation for data cataloguing and governance
  • Tableau and Power BI for business intelligence and visualisation
  • Dataiku for data science collaboration
  • Azure Data Lake Storage Gen2 for raw data storage
  • Event streaming architecture using Apache Kafka

Implementation Costs

  • Snowflake and cloud infrastructure: £22 million (3-year contract)
  • Data integration and ETL tools: £8.5 million
  • Business intelligence and visualisation: £6.2 million
  • Data governance and security: £4.8 million
  • Professional services and implementation: £18.5 million
  • Internal team costs: £12.6 million
  • Training and change management: £3.8 million
  • Total investment: Approximately £76.4 million

Implementation Duration

  • Assessment and strategy phase: 4 months (March-June 2019)
  • Vendor selection and architecture: 3 months (July-September 2019)
  • Foundation build and data platform setup: 5 months (October 2019-February 2020)
  • Initial domain migrations:
    • Customer data domain: 6 months (March-August 2020)
    • Product data domain: 4 months (May-August 2020)
    • Supply chain data domain: 7 months (September 2020-March 2021)
    • Finance data domain: 5 months (January-May 2021)
  • Advanced analytics implementation: 8 months (April-November 2021)
  • Legacy decommissioning: 6 months (September 2021-February 2022)
  • Optimisation and scaled adoption: 12 months (March 2022-February 2023)
  • Total duration: 4 years (March 2019-February 2023)

Savings and Benefits

  • Annual technology cost reduction: £14.2 million (40% reduction from legacy systems)
  • Reduced data processing time from 24+ hours to under 30 minutes for key reports
  • Improved forecast accuracy by 32%, reducing waste by £65 million annually
  • Personalisation capabilities driving 8.5% increase in basket value for targeted customers
  • Supply chain optimisation delivering £120 million annual inventory reduction
  • 360-degree customer view enabling 18% improvement in marketing campaign effectiveness
  • Data analyst productivity increased by 60% through self-service capabilities
  • Query performance improved 200x for complex analytics
  • Data governance incidents reduced by 85%
  • Carbon footprint reduction of 45% for data workloads through cloud optimisation
  • Five-year ROI of 380% with breakeven achieved at 26 months