Accelerating Data Product Time to Market and Enabling Data Engineering Best Practices in Azure

  • Delivery of data engineering product and solutions required significant time

  • No clear path on how to implement data solutions for the cloud

  • Guidance needed to implement software development best practices like iterative development, testing, automation of infrastructure, and reusable components

  • Desired a solution that would support data engineering projects for reusability and introspection

  • Accelerated time to value from inception to completion for data engineering projects

  • Enabled a deep understanding of software engineering best practices and key points to look for by industry professionals not typically versed in software development

  • Provided reusable frameworks for developing data engineering projects

  • Standardized mechanisms for reporting and visualizing data lineage and data pipeline metadata

  • Helped develop an understanding of how O&G can utilize technologies commonly used across other data-driven, digital-first industries

  • Improved operational capabilities of the organization to deliver data-focused solutions

  • Analyzed existing projects, processes, and paid specific attention to areas contributing to delays or causing later impediments

  • Provided recommendations for following software engineering best practices across development, testing, and deployment using iterative development and adjusting for organizational constraints

  • Recommended and implemented reusable libraries and infrastructure for data engineering management and metadata collection, creating a mechanism for collecting and analyzing data lineage across various data engineering pipelines and systems

  • Azure DevOps

  • Azure Application Insights

  • Azure Cosmos DB

  • Azure Functions (Python)

  • Swagger, Node.js, D3.js, Vue.js

  • Hashmap Consulting Services:

    • Data & Cloud Strategy & Modernization

    • Solution and Technology Guidance and Roadmaps

    • Data & Cloud Optimization and Management

    • Data Lineage Assessment and Guidance