Case Studies

GDPR Compliance

Client: Building Society

Function(s): Credit Risk, Data Management, Data Warehousing


  • Migrate from an Oracle data-mart to a GDPR-compliant SAS® data-mart;
  • Automate monthly data load; and,
  • Create an automated process to apply data-retention policies to personal data.



  • Multi-phase approach that supported separable deliverables with reduced complexity, discrete test stages and iterative releases;
  • GDPR data-separation dynamically generated from metadata allowing for faster iterations through test cycles;
  • Flexible and extendable data-purge process that executed automatically, enforced data retention policies and maintained audit trails; and,
  • Monthly processes integrated within the existing batch schedule, incorporating restart and rollback capabilities.

Data Centre Migration

Client: Financial Services

Function(s): Change Delivery, IT Systems, SAS Architecture, Platform Configuration


  • Migrate all SAS platforms, systems and data from incumbent data centres to replacement data centres;
  • Minimize operational disruption at cutover; and,
  • Ensure no gaps in data processing schedules or output generation.



  • Multiple, version-specific, SAS platforms built and configured;
  • Multiple, version-specific, SAS batches migrated and adjusted to support target environments;
  • All SAS environments and processing integrated with new source and target systems;
  • All SAS elements validated and assured prior to go-live; and,
  • Cutover plan formulated, coordinated and executed to ensure zero-impact to business operations.

SAS Platform Consolidation

Client: Lending Administration

Function(s): IT Systems, Platform Configuration, Business Intelligence, Management Information, Data Management, System Administration


  • Consolidate multiple SAS platforms into a single instance to reduce run-costs, simplify platform management and provide alignment to the target operating model.



  • Updated configuration and security model to support new data sources and outputs;
  • Rationalised existing warehouse processes;
  • Provided support to individual business units with adjustments required for their SAS components and general preparedness for go-live;
  • Migrated SAS self-serve reporting via a metadata-driven partial-promotion process;
  • Adjusted or rebuilt existing warehouse processes to function correctly on new SAS grid based platform;
  • Built automated process to upgrade and validate all SAS files from 32-bit to 64-bit and move them to new file-system locations;
  • Extensive testing and validation conducted to ensure all reporting, batch jobs and interfaces were as expected; and,
  • Transition to target platform achieved with minimal disruption to the business.

Supply Chain Management

Client: Building Materials Provider

Function(s): Business Intelligence, Operations, Finance


  • Create self-serve reporting capability for new bespoke inventory management and logistics system; and,
  • To run against the operational system and not a data warehouse in order to provide up-to-minute information.



  • Created and configured environments to support separate development, test and live activities;
  • Delivered browser-based ability for users to run reports against real-time data to support activities such as invoice generation; and,
  • Implemented overnight batch reporting that automatically produced and printed pick-lists for each branch to action upon opening.

Systems Analysis & Data Mapping

Client: Mortgage Provider

Function(s): Change Delivery, Operations, Finance, Management Information


  • Accurately map customer and account information from one mortgage administration system to another;
  • Ensure continuity of service and account processing in line with T&Cs and customer expectations on the target system; and,
  • Ensure continuity of internal and external Management Information reporting.



  • Identified all data items required to support system-based account processing and associated data-driven business processes;
  • Defined the necessary transforms to map each data item from the source to target application databases;
  • Undertook cutover and implementation planning exercises, and determined additional data manipulations required to support the real-time execution of the migration;
  • Designed and built a multi-point reconciliation process to validate the migrated data at a record (eg customer, account, transaction) level;
  • Quantified the impact on internal and external Management Information reporting as a result of the data migration and/or differences in the processing logic employed by the source and target applications; and,
  • Performed gap analyses and process reviews on the target system with regard to data and reporting, plus their downstream impact on Operations and other business functions, leading to the identification of further data/reporting requirements to close the gaps.

Warehouse Optimisation

Client: Insurance Retailer

Function(s): Data Management, Data Warehousing, Change Management


  • Implement strategy to reduce the impact of late arriving data, expansion in data volumes, long-running batches and unavailability of the data warehouse to internal teams.



  • Additional data-tier was introduced to support the separation of data-warehousing and analytics workloads to reduce contention of server resources;
  • Data warehouse processing was reengineered to increase parallelisation, optimise efficiency and augment automation;
  • A robust test-strategy of parallel running was designed and executed to identify differences between old and new processes and drive rapid and assured development; and,
  • Warehouse processing time was reduced by more than 50% and the introduction of a dedicated data-tier for warehouse users provided successful shielding from batch-related issues.