British Land boosts reporting 3.5x and cuts costs with modern analytics platform | Firemind
Case study

British Land boosts reporting 3.5x and cuts costs with modern analytics platform

Industry: Real Estate

About

Maidstone Borough Council serves nearly 200,000 residents in Maidstone, UK, providing essential public services such as benefits, recycling, and council tax management.

Challenge

British Land relied heavily on an on-premise analytics infrastructure that struggled to keep up with the demands of a growing property portfolio. Frequent hardware failures and escalating maintenance costs made the existing setup both unreliable and expensive to operate. Accessing and processing data was slow, which limited the ability of teams across the business to generate timely, accurate reports.

This lack of scalability meant that as British Land’s operations grew, so did the inefficiencies. Without a modern, cloud-based solution, the company risked further delays in financial reporting, reduced visibility into property performance, and a growing strain on internal resources.

Solution

Firemind migrated British Land’s analytics to a scalable AWS cloud environment, replacing legacy infrastructure with a secure and resilient platform. At the core of the solution was the integration of Qlik Sense to deliver highly interactive, custom dashboards, enabling self-service analytics for teams across the business.

To ensure data pipelines were reliable and automated, AWS Glue and Amazon Kinesis were deployed, allowing real-time data ingestion and transformation. Amazon QuickSight was then used to create rich visualisations, offering both operational and financial insights at speed. This modernised analytics approach eliminated the bottlenecks of the old system while enabling faster, data-driven decision-making across the organisation.

Services used

  1. Amazon Redshift
  2. AWS Glue
  3. Amazon Kinesis
  4. Amazon QuickSight

Results

  • 3.5x increase in data reports
  • 2.5x more advanced reports
  • Faster financial insight generation
  • Reduced infrastructure costs
  • Fully scalable analytics platform

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