Case study

Data Migration & Engineering

Media, Telecommunications

Forecast delivered several technical aspects that added value to the client, including a new data structure that allowed for better analysis of current and future value-add projects.


Our client is a provider of subscription television, internet, and mobile services. They have an international reach totalling over 22 million customers and a history of developing innovative products and entertainment content.


Our client was looking to increase the utilisation of the core data consumed in their on-site data warehouse and any transformation logic used by migrating the data into Google Cloud Platform (GCP). The aim of this was to increase the usefulness of the data and to be able to respond quickly to change requests to the data structure. As this data was becoming increasingly transformed and transported by our client, the complexity of managing this infrastructure quickly increased. Our client required robust pipelines to be implemented to manage this extra complexity without errors.


Forecast worked with the client to develop a data structure that was better aligned with the existing business reporting and to include key metrics of interest to the client. Additionally, Forecast designed an automated process to streamline the data transfer from their on premises data warehouse to GCP.


Forecast delivered several technical aspects that added value to the client, including:

  • A new data structure that allowed for better analysis for current and future value-add projects. This included daily and monthly customer data scaling to multiple Terabytes, where business-applicable metrics could then be derived.
  • Automating data transfer processes on robust pipelines – moving from a manual to an automatic schedule. This decreased the total time involved from days to hours.
  • A combination of cloud infrastructure (GCP), Python and Windows Batch scripting was used to build a custom tool, specific to the client’s environment.
  • The amount of comprehensive data in GCP enabled Forecast to use various advanced technologies on further projects.

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