Deputy is a SaaS company providing workforce management and rostering/scheduling solutions for shift workers worldwide.
The Data team at Deputy were looking for a platform to build and maintain a Data Model to support the existing BI and analytics platform.
Deputy’s data team partnered with Altis to build a data model to support the Dashboard and Business Processes and establish a data integrity framework which would allow accuracy and governance of data throughout the Data Warehouse.
The Data being used for reports and dashboards was transformed in Snowflake tasks within various databases which were untracked. With the growth of the company, this took an increasing amount of time and resources to process, which then hindered the performance of important business dashboards and reports and also accrued additional costs.
Altis recommended a data model to make business processes clearer, along with implementing dbt cloud in the technology stack for the maintaining, transforming and build of the data model.
dbt cloud integrated with Github and Snowflake to provide version control and maintain traceability for both the code and data. Software Engineering best practice was implemented i.e. Pull Requests, Code Review, Test Environments and CICD.
Data integrity and governance were handled by dbt cloud with features such as generic tests, dbt documentation and data lineage.
Separate deployment and development environments help maintain data quality and make resolving issues faster and more efficient.
“The data transformation at Deputy would not have been possible without Altis and their support. They were able to come in and add the fundamentals back into our processes and help the business trust the data, in such a short space of time. I can’t recommend Altis enough to anyone that is about to embark on a transformation, especially with the roll out of a tool like dbt.”
– Huss Afzal – Director of Data – Deputy
Altis along with data team delivered the data model across 2 development waves (Sales and Finance). The type 2 dimensions helped deputy capture history across business processes which helped the business discover insights which weren’t previously possible.
All environments are distinct and with a code convention and deployment strategy in place, the data team were able to deliver more accurate and efficient dashboards. More robust control of data led to a reduction in resource utilisation.
Tableau reports and data load times also improved with the dimensional model.
Furthermore, incidents and errors within the environment are reported and resolved much quicker with reporting and logging of data issues in dbt cloud.
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