As Travel Chapter’s data demands grew as a company, its on-premise SQL server was running out of room. With upgrades to server capacity being costly, however, both in terms of downtime and investment, and with subsequent increased demand for computing power being potentially inconsistent, such a move to develop the existing data warehouse posed serious questions for the business, in terms of efficiency and cost-efficacy.

The existing setup also led to data reporting which was reactive in nature, rather than proactive or predictive, which was something the data team wanted to rectify.

Accurate predictive models typically require large quantities of data, however, which, again, was something the existing server configuration was almost certainly going to struggle with.