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United States
51 - 200
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Profisee is how enterprises can finally solve the data quality issues that have been holding back so many strategic initiatives. Too often, it can feel like every time you start to make progress on your Digital Transformation, or ERP implementation, or disruptive new marketing campaign, bad data stops you in your tracks. To get past this brick wall, you need a smarter approach to data management. That’s what Profisee brings, with our “make it easy, make it accurate, make it scale” approach. Our cloud-native MDM solution fully cleans and unifies data for you, and can easily scale up, down, and across your different business functions — so you can finally make it happen. Profisee operates directly in the United States, Europe and Australia — as well as through a network of Value-added Resellers (VARs), Systems Integrators (SIs) and world-class Professional Consulting firms across the globe — and offers customers 24/7 support. To learn more, please visit Profisee | Now you can make it happen.™

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Profisee.’s Technology Stack maps Profisee.’s participation in the IoT technology stack.
  • Application Layer
  • Functional Applications
  • Cloud Layer
  • Platform as a Service
    Infrastructure as a Service
  • Edge Layer
  • Automation & Control
    Processors & Edge Intelligence
  • Devices Layer
  • Robots
  • Supporting Technologies
  • Analytics & Modeling
    Application Infrastructure & Middleware
    Cybersecurity & Privacy
    Networks & Connectivity
Technological Capability
Number of Podcasts1
EP 161 - How to maintain data quality across systems - Malcolm Hawker, Chief Data Officer, Profisee
Wednesday, Feb 01, 2023

This week, our guest is Malcolm Hawker, Chief Data Officer of Profisee. Profisee is a cloud-native master data management solution that helps enterprises solve data quality and governance issues.

In this talk, we discussed the challenges related to data management, from integration between systems to standardizing workflows. We also explored how blockchain can impact data governance by making it easier to manage data sharing between supply chain partners.

Key Questions:

  • How do you segregate jobs to be done in data management?
  • What are the distinct challenges for each platform and data set?
  • How centralized does network data mover tend to be?


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