Cloud Scale Analytics ​Implementation


A complete development lifecycle that results in a fully working solution

What you can expect?

Analytics Lifecycle: Develop a Central Data repository that includes
40 Reports and 10 PowerBI Dashboards (2 to 3 data sources) Requirements analysis and project scoping Identification of data sources required, explorative data analysis, conceptual design of data lakes Building target-oriented Data Analytics architectures with batch and/or real-time processing as well as streaming Selection of appropriate technologies and services, focusing on scalability, maintainability and operating cost optimization Azure migration of existing Data Analytics platforms Connecting on-premises data sources to Azure Automation of Data Analytics processes (orchestration) & DevOps

Approach Envision: Analyze current infrastructure and environment Plan: Design optimal data estate based on our knowledge of Azure Build: Design and Develop infrastructure Stabilize: Validate feedback, iterate & improve Deploy: Test for durability & scalability, Plan for long-term operations and Documentation and Training

Deliverables 40 Reports and 10 PowerBI Dashboards Agile Project Management Client team enablement Build a foundation for future value-added increments Development of backlog to continue to drive value Data scenarios and source system data integrity validation Ability to perform self service analysis A modern data platform in Azure Complete testing and sign-off your Azure data environment for production use Skill transition completed with your internal team, or transition to our data platform and insights managed services