Gain Visibility And Insight Into Your Supply Chains Through Operational Analytics Powered By Roambee
Data Engineering Podcast
Predictive Capabilities
We are in the business of visibility, right? So we know our device when it moves out of a location. We know through a lot of interesting ML and things like that, that's been the origin and the shipment has started. And let's say from that origin, based on the patterns that we have seen in the last six, seven, 10 months, there are eight destination origin destination pairs. But as the journey starts progressing, we start basically short listing those origin destination pairs,. It's basically getting shortlisted to a point where now we have absolute clarity through our technology that the destination is 100% point B and not point C. This is built into using some very interesting probability theories
Summary
The global economy is dependent on complex and dynamic networks of supply chains powered by sophisticated logistics. This requires a significant amount of data to track shipments and operational characteristics of materials and goods. Roambee is a platform that collects, integrates, and analyzes all of that information to provide companies with the critical insights that businesses need to stay running, especially in a time of such constant change. In this episode Roambee CEO, Sanjay Sharma, shares the types of questions that companies are asking about their logistics, the technical work that they do to provide ways to answer those questions, and how they approach the challenge of data quality in its many forms.
Announcements
- Hello and welcome to the Data Engineering Podcast, the show about modern data management
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- Your host is Tobias Macey and today I’m interviewing Sanjay Sharma about how Roambee is using data to bring visibility into shipping and supply chains.
Interview
- Introduction
- How did you get involved in the area of data management?
- Can you describe what Roambee is and the story behind it?
- Who are the personas that are looking to Roambee for insights?
- What are some of the questions that they are asking about the state of their assets?
- Can you describe the types of information sources and the format of the data that you are working with?
- What are the types of SLAs that you are focused on delivering to your customers? (e.g. latency from recorded event to analytics, accuracy, etc.)
- Can you describe how the Roambee platform is implemented?
- How have the evolving landscape of sensor and data technologies influenced the evolution of your service?
- Given your support for customer-created integrations and user-generated inputs on shipment updates, how do you manage data quality and consistency?
- How do you approach customer onboarding, and what is your approach to reducing the time to value?
- What are the most interesting, innovative, or unexpected ways that you have seen the Roambee platform used?
- What are the most interesting, unexpected, or challenging lessons that you have learned while working on Roambee?
- When is Roambee the wrong choice?
- What do you have planned for the future of Roambee?
Contact Info
Closing Announcements
- Thank you for listening! Don’t forget to check out our other shows. Podcast.__init__ covers the Python language, its community, and the innovative ways it is being used. The Machine Learning Podcast helps you go from idea to production with machine learning.
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Parting Question
- From your perspective, what is the biggest gap in the tooling or technology for data management today?
Links
The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA
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