Modernization with Azure Databricks Data Intelligence Platform: 4-Week PoC

WinWire Technologies

Experience the value of Azure Databricks with WinWire

Databricks Data Intelligence Platform is a scalable and unified data solution that offers big data processing, GenAI, AI & machine learning, and advanced analytics all within a collaborative environment. It integrates seamlessly with Microsoft Azure's cloud services to provide a powerful, scalable, and secure data analytics platform. This platform can greatly enhance productivity, collaboration, and provide advanced insights at scale.

WinWire’s Proof-of-Concept (PoC) on Azure Databricks Platform

The goal of this 4-week PoC is to show how your organization can implement and adopt Azure Databricks, meet business objectives, and improve data operations. This can be achieved through a new deployment or by migrating from legacy systems, while transitioning from on-premises or traditional cloud-based data warehouses.

Key Benefits

  • Cost Saving: Native integration with Azure ecosystem and a unified experience with integrated security and governance to ensure significant cost savings.
  • Tailored to Your Business: The PoC caters to your specific data, KPIs, and business goals.
  • Rapid Implementation: Get a working Azure-Databricks environment in only 4 weeks, with actionable insights.
  • Scalable Solution: Establish a scalable, high-performance solution to handle growing data volumes and complex use cases.
  • PoC Approach

    Week 1: Discovery and Assessment

  • Stakeholder Interviews: Sessions with business and technical stakeholders to understand current pain points, data challenges, and strategic goals.
  • Data Landscape Review: Assessment of the existing data infrastructure, architecture including batch and streaming pipelines, storage, processing units, BI and AI-ML services.
  • Define PoC Objectives: Measurable goals for performance metrics, business outcomes, and functional requirements.
  • Compliance & Security: Evaluating governance, security, and compliance Al requirements.
  • Week 2: Architecture and Design

  • Solution Architecture Design: Tailored to your specific use cases.
  • Data Ingestion and Processing Strategy: Efficient data pipelines for batch/streaming processes.
  • Cloud Integration Planning: Strategies for network, storage, compute and cost optimization.
  • Data Governance and Security Setup: Policies for data governance, role and attribute-based access control, column-based masking.
  • Week 3: Implementation and Migration

  • Environment Setup: Validation of the Azure Databricks workspace, clusters, and configurations.
  • Data Ingestion & Pipeline Setup: Loading batch and streaming data onto the Azure Databricks platform.
  • Initial and ongoing Data Processing: Validation of performance, efficiency, and resource utilization.
  • Integration with BI and AI Tools: Existing reports and dashboards and AI-ML are connected and new Databricks AI and BI services are set up.
  • Week 4: Validation, Testing, and Finalization

  • End-to-End Testing: Data pipelines, workflows, visualizations, AI-ML adhering to performance, speed, and accuracy goals.
  • Workload Optimization: Review of cluster usage, pipeline efficiency, and resource consumption to ensure Azure Databricks platform is cost-effective and scalable.
  • Security & Compliance Validation: Data governance, security, user administration, access management, compliance & monitoring requirements with Databricks Unity Catalog and Microsoft Purview (optional).
  • Training & Knowledge Transfer: Hands-on training sessions to your technical and business teams, enabling them to manage the Azure-Databricks environment, run workloads, and build visualization and AI-ML models.
  • Scale-out Recommendations: Comprehensive report outlining the findings of the PoC. An Enterprise-wide roll-out plan for the adoption of Azure Databricks.
  • PoC Deliverables

    • A fully deployed and tested Azure-Databricks environment.
    • Lakehouse architecture implementation and documentation.
    • Data pipelines migrated and built from scratch.
    • Representative AI/BI visualization and AI-ML serving.
    • Data governance with cataloging, classification, discovery, auditing, lineage.
    • Training sessions for your team on Databricks and Azure best practices.
    • Final PoC report with key findings, recommendations, and next steps
    • A scale-out plan for enterprise wise adoption of Azure-Databricks platform and services
    • Contact us to discuss how Azure Databricks can help your enterprise leverage the power of data intelligence and accelerate your journey to the cloud. Leverage our rapid 4-week PoC to experience the value of Azure Databricks Unified Data Intelligence Platform for deep business insights.

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