Improving Operational Decision Making Within Airport Security Operations

Manuka supported Manchester Airport Group on its initial journey towards using AWS for its data and analytics platform. Carry on reading to find out more about the project and case study.

MAG’s Dev Ops approach and detailed knowledge of all aspects of AWS data services made sure that we could get production workloads running in AWS within 12 weeks of project inception. Manuka has continued to support the MAG expansion of using data on AWS. We’re now working with MAG on a number of data implementations in the cloud. This covers improving Retail insights with visualisations and real-time data pipelines in operational areas.

About Manchester Airport Group

The Manchester Airports Group (MAG) umbrella consists of the operations of Manchester Airport, alongside London Stansted and East Midlands. Additionally, MAG Property and Cargo Operations also come under the remit of our brand, representing Manchester Airport as the global gateway to the North of England and beyond. Manchester Airport has won prestigious industry recognition for customer service, and holds the title of ‘Best UK Airport’

The Challenge

MAG already have a mature stack of BI and database products for reporting however these were reaching the limits. This requires a replacement that will create an extensible and flexible data solution, allowing MAG to reach its ambitions. The new solution would need to enable an extended Data Warehouse, scalable and elastic compute, deal with seasonality spikes of passenger travel and allow real-time streaming of data; empowering MAG to become a real-time business across their entire customer journey.

Why Amazon Web Services

Manchester Airport Group wanted a secure, resilient environment with repeatable build patterns and Amazon Web Service was perfect for this. “We wanted to create an architecture that can evolve over time to meet MAG’s new challenges delivering benefits early and continuously without the need for MAG to invest in a large, front-loaded enterprise Data Warehouse programme,” says Stuart Hutson Chief Technical Office (previously the Head of BI at the initiation of the project). The MAG AWS environment includes Redshift, Kinesis, S3, SQS, SNS, CloudWatch, CloudTrail, ECS, EC2, RDS, Config Service as well as other AWS Services.

The Benefits

In the first 6 months of the project, MAG went from a single instance database to a scalable Data Warehouse. This was done by using Redshift. Daily sales rang in at store level to over 90% of all sales automatically ingested at the product level. This came from over 50 separate retailers such as Dixon, Burger King, Hugo Boss, WH Smiths etc.

Reports access was via a reporting tool to authorised users, who were able to visualise data and use data science tools such as R and Python for self-server analytics. This came from no ability to create and run their own SQL to sandboxes within the scalable Redshift environment.

By the end of the first year, MAG had added a real-time streaming solution to ingest data from the car park and fast-track bookings to the data warehouse. This was done by using Kinesis and Lambda. In addition, by the end of the second year, they had multiple real-time dashboards. These were shown on TV screens in their control room showing the real-time customer security queues. Dashboards were ingesting data from dozens of sources including trains, queues, metal detector scans, body scans, x-rays etc.

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