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Compare WizzDev vs DQO

Side-by-side comparison of features, pricing, services, ratings and more.

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WizzDev Agency logo

WizzDev

Data & Analytics Website

WizzDev has extensive experience in the development of Internet of Things systems, laboratory automation software, and bespoke instrument control software ranging from Live Science to Automotive industries. The agency provides turnkey and customized solutions for home automation, bio-science, life-science, automotive, and intelligent transportation systems. Past clients include DNA Electronics, Oxford Nanopore Technologies, Mursla, Cetoni, Mill, Costain, and Illumina.

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DQO Agency logo

DQO

Data & Analytics Website

DQOps is an open-source data quality platform designed for data quality and data engineering teams that makes data quality visible to business sponsors. Founded in 2020, DQO is headquartered in Warsaw, Poland.

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Feature Comparison

Attribute WizzDev DQO
Category Data & Analytics Data & Analytics
Rating
Winner +5.0 higher
-
Location Poznan, Poland Warsaw, Poland
Services
  • IoT
  • Software Development
  • Cloud Consulting
  • Mobile App Development
  • DevOps Consulting
  • Wearables
  • Web Development
  • Software Testing
  • AI Development
  • Big Data Analytics
  • Data Quality Monitoring
  • IoT
  • Software Development
  • Cloud Consulting
  • Mobile App Development
  • DevOps Consulting
  • Wearables
  • Web Development
  • Software Testing
  • AI Development
  • Big Data Analytics
  • Data Quality Monitoring
Industries
Software & IT Services Automotive Health Care Home & Garden Agriculture Electronics Hardware & Networking Entertainment Transportation & Logistics Government
FMCG Public Health
Pros
  • Extensive experience in IoT systems, laboratory automation, and bespoke instrument control
  • Proven track record with clients like Oxford Nanopore Technologies and Illumina
  • Expertise in cloud computing with AWS, Azure, and Egnyte
  • Positive Google review highlighting professionalism and world-class specialists
  • Open-source platform with over 150 built-in data quality checks and support for custom checks
  • DevOps-friendly with YAML-based definitions in Git, pipeline execution, and a Python client
  • Deployable locally or as a SaaS platform
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