Streamline your data pipelines to support real-time decision-making capabilities. Deploy best practices across your Big Data stack.

  • Prototype Development

    An iterative approach through quick proof-of-concepts will help validate your Big Data innovations faster than a waterfall approach.

  • Repeatable Deployments

    Go from Jupyter Notebooks to Cloud-native containers. Automate the delivery of your pipeline using Continuous Integration/ Continuous Deployment (CI/CD). Prevent drift in your architecture using Infrastructure as Code (IaC) tools like Terraform.

  • Observability

    Improve your ability to troubleshoot issues, and find performance bottlenecks by adding instrumentation in your ETL process. Roll up the data into dashboards for real-time decision making.

  • Data Pipeline Optimization

    Simplify and modernize your data pipeline: move away from batch processing and implement real-time streaming into your data lake.

End-to-End Quality

Professional methods and tools to ensure robustness, dependability, functional safety, cybersecurity and usability:

  • Agile process
  • CI/CD
  • DevOps pipelines
  • Secrets management
  • Source control management
  • Automated testing
  • Documentation
  • Instrumentation
  • Monitoring

Technology Expertise

20+ years of software development and deployment experience with a focus on:

  • Python
  • Django
  • Flask
  • Plone
  • React
  • PostgreSQL
  • Redis
  • Docker
  • Salt
  • Terraform
  • AWS
  • GCP

How to Engage with Us

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Vision Builder™

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Technical Planning

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Collaborative Development

How will we Make Anything Possible™?

Proactive Support

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Strategic Planning

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Past Projects

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Latest Blog Posts

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Hacking Django Channels for Fun (and Profit)

LoudSwarm by Six Feet Up, a Django-based virtual event platform, has always supported Slack for instant, in-app text communication. In addition to Slack, clients were requesting Discord integration, so Six Feet Up’s expert team of developers found a solution.

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How to start with Machine Learning

Machine Learning initiatives can be powerful when you need to analyze large amounts of data, especially when it makes sense to analyze data points together to gain greater insights or find patterns...

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