![]() What is our minimum viable product? What are our blockers? IAM permissions and stopping and starting. With this greenfield project using my consulting hat, I helped our stakeholders develop the first use case, iterate and develop the next one and so forth. Using a Miro board to sketch the high level architecture (it's ok to draw what you think might be the final solution and then consult and iterate) collaborating with platform teams and also consulting with AWS to develop a solution using AWS Cloud Formation template. ![]() By understanding the current state we wanted to create a vision of the end state and how to improve customer experience for NSW citizens. Working in a sprint fashion, this greenfield government project included test, build and deploy. One of our initial questions on the journey with AWS included how do we store all of this data? How do we create a data lake to also bring in external data from another data lake? In a busy contact centre we serve customers and generate petabytpes of data in structured and un-structured data formats. The AWS services used to build our analytics roadmap were: With lake house architecture we integrated a data lake, data warehouse and business intelligence with security, performance, elasticity, data velocity, cost effectiveness and governance to design a unified analytics platform for our organization-wide data architecture roadmap.Īmazon Redshift has massively parallel processing (MPP) for fast and complex queries and can analyze all our data. We built a well-architected modern data analytics pipeline with a fully-managed, petabyte-scale cloud data warehouse using Amazon Redshift under the Department of Customer Service using AWS Organization.
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