Data modernization and requests done 4 X faster
Laborious SQL server maintenance mitigated
Enables scaling with more confidence, accuracy and effectiveness
About
Travel Chapter is among the UK’s most highly-regarded holiday letting agencies, showcasing a wonderfully diverse portfolio of properties across the nation. Having grown from a small south-western lettings agency, established in 1989, Travel Chapter has gone on to become a leading nationwide agency, partnering with a carefully- curated selection of premier holiday home brands, whilst always ensuring that the family ethos that started it all remains front and centre in everything they do.
We’re able to react to what the business wants faster today, than ever before. In the past, we had to fix manually what was an ancient data warehouse before we could give stakeholder the data they wanted. We migrated around 300 tables using Kleene into Snowflake. We now
have around 200 transformations and we don’t have duplicate information
Andrew Jenkins (Head of Data) Travel Chapter
The Challenge
Legacy SQL data warehouse struggling with scaling business demands
Legacy SQL data warehouse struggling with scaling business demands SAs 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.
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.
The Solution
Modernising to Snowflake with Kleene’s data warehouse tool
Utilising Kleene’s cloud stack solution as an alternative to the company’s legacy SLQ data warehouse has enabled more data to be processed more quickly – quickly in every sense: the company’s data warehouse has been growing quickly, data has been able to be communicated to people within the business more quickly, and therefore feedback has been able to be generated from said data morequickly.
The Results
More data coming in
With the implementation of Kleene, Travel Chapter has been able to work with larger quantities of data than in previous years, and do so without fear of inaccuracy or slow throughput.
“So much data is coming in, which is fantastic for us because I’ve always felt [in the past] like we’ve been the blocker. Whereas now, it’s a case of ‘what other information do you want?’”
Data consolidation
With Kleene’s platform, the company has been able to better consolidate their, so as to avoid duplicate information, in effect doing “more with less”.
According to Travel Chapter’s Andrew Jenkins, using Kleene’s tool was “so easy” and freed their team up to focus on the aspects of data managed they found more rewarding and useful.
According to Travel Chapter’s Andrew Jenkins, using Kleene’s tool was “so easy” and freed their team up to focus on the aspects of data managed they found more rewarding and useful.
"The team haven’t had to worry about indexes since we’ve started using Kleene. They love that. They can just carry on doing the stuff they enjoy. Kleene is literally doing everything that we're having to manually build."

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