Data Warehouse Implementation - Azure Databricks and ADF

Service Overview:

AVASOFT offers a comprehensive Azure Databricks and Azure Data Factory (ADF) implementation package tailored for organizations encountering data challenges. We specialize in creating private Databricks infrastructure in Azure with all necessary networking components to connect with on-prem data sources. Additionally, we set up DevOps CI/CD pipelines for seamless infrastructure deployment and code promotion across environments, utilizing Azure DevOps CI/CD tools. Our solution incorporates leveraging ADF as both an Extract, Transform, Load (ETL) tool and a connector for data sources not compatible with Databricks, ensuring extensive data integration capabilities.

Key Features:

• Private Infrastructure Provisioning: Provisioning private Databricks infrastructure in Azure with seamless connectivity to on-prem data sources.
• DevOps CI/CD Setup: Configuration of DevOps CI/CD pipelines for automated infrastructure deployment and code promotion.
• ADF Integration: Utilization of Azure Data Factory for ETL operations or as a connector for data sources not supported in Databricks.
• Seamless Connectivity: Establish robust networking components to ensure seamless connectivity between Databricks and data sources.
• Tailored Solutions: Customized solutions to meet the specific data challenges and infrastructure requirements of each organization.

Deliverables:

• Detailed Deployment Plan: A comprehensive plan outlining the steps for provisioning Databricks infrastructure, setting up networking components, and configuring DevOps CI/CD pipelines.
• Azure DevOps Integration: Configuration and setup of Azure DevOps Build and Release Pipelines for automated infrastructure deployment and code promotion.
• Application Deployment: Successful deployment of Databricks infrastructure and ADF configurations, ensuring secure hosting and performance.
• Monitoring and Analytics Configuration: Configuration of monitoring and analytics tools to track infrastructure performance, identify issues, and drive continuous improvement.

Next Steps:

• Performance Optimization: Conduct performance testing and optimization to ensure efficient data processing and application performance.
• Continuous Improvement: Establish processes for continuous monitoring, analysis, and optimization of infrastructure performance and cost efficiency.