We supported the data science team of our client who was looking to improve the delivery of analytics reports to help managers make informed business decisions.
The financial sector is experiencing severe competition and organizations that want to thrive need to be quicker and smarter in acquiring insights from data to make data-driven business decisions. Our client was looking for software developers who would support the internal data science team with Python expertise and know-how. The primary business goal was developing a system that would enable to deliver analytics reports quickly and efficiently to support the decision-making process at the organization.
The first step of our team was the implementation of data pipelines. We then migrated the organization’s data to a new data warehouse. Throughout that process, we were also responsible for supporting the client's internal team of data scientists in completing various tasks and sharing best practices in the field. We advised the client about the choice of programming tools such as CI, repository organization, and linters through their evaluation and consultancy in reference to the planned infrastructure for the implementation of Airflow.
We have completed a data warehouse migration, going from Athena to Snowflake. The client’s team can now work with data more efficiently and with greater comfort. Moreover, we have released our own instance of Apache Airflow for automating data processing. Our team helped in implementing Continuous Integration/Continuous Delivery (CI/CD) practices and shared other relevant know-how with the client’s team of data scientists.
Successful data pipelines implementation
Successful data warehouse migration to Snowflake
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