How Adding Context to Your Data Can Transform Your Business
ฝัง
- เผยแพร่เมื่อ 20 มิ.ย. 2023
- Walker Reynolds from 4.0 Solutions goes over what Additive Data Context is, and what the step to data ops are.
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#IIoT #Industry40 #DigitalTransformation - วิทยาศาสตร์และเทคโนโลยี
This architecture is fully scalable and can be applied from the biggest multinationals to the smallest sensor. Great presentation!
Content is great, as always.
Just my 2 cents of feedback - my personal all-time favorite video was titled “How to implement OEE in your manufacturing plant” 3 years ago ONLY because you used transparent glass “whiteboard” with multicolor pen (mainly green/white/pink/red) in a completely pitch-black background. You were writing behind the glass, whereby our view of the material you wrote was never obstructed at any time.
It was difficult to follow along here ONLY because you were covering the “whiteboard”. I have no idea how you did the transparent glass video (all magic to me), but I loved it because I could see everything, and it clicked better in my brain to see what the instructor writes while they are talking. I like being able to see both the instructor and the notes simultaneously all the time with nothing obstructing them.
Thanks in advance!
Thank you for the feedback! We’ll see about capturing the video of the vibe board and overlaying it
I loved this one. I wanted to know more about the challenges of implementing this to large enterprise, which in my case is heavily driven by Camstar, SAP (moving to S4 hana), Maximo, Windchill PLM, Kepware, vendors wanting you to buy Mindsphere, Thingworx, etc and with digital thread mindset (Azure) which I don’t believe it is going to work and provide real-time data unless they review architecture and use open, light weight, edge driven solutions, like I would believe node-red could be a starting point
It's great learning about the Unified Namespace from different angles. You're giving us good vibe rations!
Please do more on this!
Will do! More whiteboards or more videos on data context?
@@4.0Solutions More data context (and other concepts) on whiteboards.
@@4.0Solutions Both! 1. As EthicsAndEnginnering said, that video execution was amazing. 2. Data context and technical details. I get that maybe not everybody will listen to it, but a bird eye overview would already be amazing. Since I've noticed that Walker has been talking about AI/ML a lot, but never actually explaining an implementation besides general building blocks (I might be wrong on this). In this video again it stops at UNS and ERP.
That is all the feedback I've, thanks for the effort and time!
Great Video! Could the link to the LinkedIn post be shared?
I like technical discussions too, it is the bridge from concept to implementation without giving away codes.
How about having subchannels like 4.0 Business Concepts and 4.0 Technical Concepts? If I am a manager that only likes business side, then I just watch the Business Concept discussions.
Got that idea from a car detailing channel that I also watch where the regular/original channel talks about detailing in general, and a new channel for a more in-depth discussion of techniques and tools, plus a longer format that might be boring to some but excellent for fellow detailers
Thank you! We can look at building playlists for the specific subtopics as well.
I'm a software engineer. I still can't understand what you try to explain.
What type of software engineering do you do? If I understand that, I can translate.
@@walkerreynolds973 most of time enterprise solutions for insurance healthcare companies.
@@CasaDeMold Ok -- so the fundamental difference between your domain and manufacturing is the ISA-95 Part 2 Model. Manufacturers are generally organized in 5 layers (or 6 layers depending on who you ask). From top to bottom, Cloud - ERP - MES - SCADA - PLC/HMI. PLC/HMI - SCADA - MES is where the manufacturing takes place, ERP and Cloud are where enterprise functions take place. What we think of as traditional 'enterprise data' or 'enterprise information' models in the commercial, retail, financial sectors are not the same as what we see in manufacturing and industry. The parameters, elements and events that make up data and information models, come from various layers in the stack (at different times) -- and this is why additive data context matters.