Our client provides expert consultancy services to commercial operators, and due diligence to investors, with a particular focus on mixed use, airports, travel, and retail property. The team help their clients by delivering expert services in commercial intelligence and quick wins; commercial strategy and vision; space planning and revenue forecasting; and investment advisory and due diligence.

The Problem

The client had a wealth of data from their clients that could be used for advanced data analytics to help understand and navigate their industry landscape. However, they did not have a dedicated data platform to help take advantage of it. This meant they weren’t able to create a data driven solution to their client’s requirements.

The Brief

We were tasked to help set up a prototype data platform with an analytics solution on top of it. This would then be showcased to their clientele, which included large airports and retail portfolio owners like Heathrow and LaSalle.

The Solution

Bigspark worked with the client to design a solution to suit their needs. The solution involved periodic ingestion of flat files or semi-structured data that was automatically tagged with ID’s to uniquely identify the client and relevant sub-sections of their portfolio. The ingested data would then go through a series of transformations and enrichments that would unlock the information hidden in the plain data in those files.

A decision was made to categorise the data points based on commercial, environmental and social impact for the client. Every asset under a portfolio was assigned a score on various metrics based on benchmarks agreed with The Client and the scores were weighted appropriately.  We finally arrived at a final health metric that not only covered the commercial wellbeing of the asset but also the environmental and social impacts.

The underlying data was then exposed through API’s for any consuming application to use. A web portal was also created to view and manage the portfolio’s performance.

Tech We Used

Azure Cloud platform
Azure Blob Storage
Azure Cosmos DB (Mongo API)
Azure Batch Account
Python Pandas library
Azure Data Factory
Azure Container Registry
GraphQL
Azure API
Next.js