One of the best videos I have ever seen about this topic ! Its so refreshing to see a person we aware of how one word can possibly have many meanings. Subscribed
Very nice explaination 🙏 A must watch video not only for every an aspiring DSc. to clear the clutter of mind thoughts, but also for the decision makers who are planning to transforming and build their institutions/companies/businesses on AI/ML/Data Science. A great thank you for making this video.
Dr Raj, thanks for this video. What would you consider to be the roles of CDOs and CIOs and CTOs in this context? Also, can you share your views about the roles that indirectly affected by AI and Advanced Data Analytics in the organization. For example, a Marketing manager who has to retrain to learn more digital marketing and so forth. Thanks.
Great question Grace. I think that the role of the CDO is critical to ensure that data is made available for the different roles in the organization to consume. After all, data is the starting point for everything analytics. The biggest problem many large companies face is getting control of their data. Typically the CIO used to play the data role but not to the extent that we need them to. I think the CIO typically has stayed at the technology stack level trying to bring together the right software, and the right platform to get businesses operating smoothly. The CTO seems to be leaning towards new technologies that can enable or bring about new products. They focus on the latest and greatest technologies for the most part. I think the perception is that the CIO focuses on the operations “current” work, and the CTO focuses on the innovative “future” work. Having said that, there's a lot of overlap among the three roles and different organizations have different people doing these tasks without necessarily have a formal position for each. On your analytics question, I think every person in the organization now needs to understand data even - though at possibly different levels. While the data scientists may have to understand data in depth, the marketing manager needs to understand how such data can be leveraged for say, digital marketing. So I think as the organization becomes more digitally savvy you'd be hard-pressed to find knowledge-based roles that don't require understanding data.
Hi Raj. Once a model has been built and deployed, its performance needs to be monitored, as does the business environment in which it operates. Events like a new piece of insurance legislation can fundamentally alter the parameters against which the model was originally developed. Is there a role in the Data Science arena that covers this kind of responsibility? Or do you see it being an operational responsibility?
Hi PG, Great question. I've found that the operational people are often not so familiar with the model, other than knowing it as a black box. So while they might be monitoring the performance of the system/model(s), it's often left to the data science people to adjust it with new data or new context as you mention above, if the model performance 'drifts.'
That's sensible Raj. It feels to me like some collaberation is required here. Business strategists and managers need to be aware that the Data Science group is now part of the bigger team, and so needs to be kept informed about strategic developments that might impact production models. A joint impact review exercise is used to transfer knowledge to the Data Science group who then pick up the model adjustment work as you describe. Business Architects are well-positioned to encourage this information flow.
Wow, In little time somuch information on Data . Simply Superb.
Excellent post on various roles related to data... I have not seen a better post on this topic... Thanks for sharing...
Thanks, Pankaj!
One of the best videos I have ever seen about this topic ! Its so refreshing to see a person we aware of how one word can possibly have many meanings. Subscribed
Glad you enjoyed it!
Great video Raj! I love the way you structured each role.
Thanks a ton!
Very nice explaination 🙏
A must watch video not only for every an aspiring DSc. to clear the clutter of mind thoughts, but also for the decision makers who are planning to transforming and build their institutions/companies/businesses on AI/ML/Data Science.
A great thank you for making this video.
Thanks so much Ronak
Best data science overview on RUclips, PERIOD! I am not exaggerating!
Thank you so much Morgan!
Great video, you really explained the data realm simply.
This is a great video. I have had this explained by others before but nothing clicked until now.
Thanks Michael!
Beautifully explained! Am glad I came across this video
Glad it was helpful!
Wow what a great explanation. Keep doing this kind of work sir. That's so helpful for a begginer like me 👍
A simple model was explained with different roles.Thank you for sharing
Perfect explanation.
Glad it was helpful!
How business extracts value from data
Thank you this was very helpful in understanding what is involved in data science.
Nice video nd well explain
Amazing summary :)
Thanks man. Very helpful
Most welcome Jose
Great Explanation. Thank you
Good one Ramesh
Please what software you use to make this animation
www.drrajramesh.com/sparkol
than you very much sir
Hi Raj, you nailed it, better start teaching Data science course full fledged
I need to find the time... :-)
Dr Raj, thanks for this video. What would you consider to be the roles of CDOs and CIOs and CTOs in this context?
Also, can you share your views about the roles that indirectly affected by AI and Advanced Data Analytics in the organization. For example, a Marketing manager who has to retrain to learn more digital marketing and so forth.
Thanks.
Great question Grace.
I think that the role of the CDO is critical to ensure that data is made available for the different roles in the organization to consume. After all, data is the starting point for everything analytics. The biggest problem many large companies face is getting control of their data.
Typically the CIO used to play the data role but not to the extent that we need them to. I think the CIO typically has stayed at the technology stack level trying to bring together the right software, and the right platform to get businesses operating smoothly.
The CTO seems to be leaning towards new technologies that can enable or bring about new products. They focus on the latest and greatest technologies for the most part. I think the perception is that the CIO focuses on the operations “current” work, and the CTO focuses on the innovative “future” work.
Having said that, there's a lot of overlap among the three roles and different organizations have different people doing these tasks without necessarily have a formal position for each.
On your analytics question, I think every person in the organization now needs to understand data even - though at possibly different levels. While the data scientists may have to understand data in depth, the marketing manager needs to understand how such data can be leveraged for say, digital marketing. So I think as the organization becomes more digitally savvy you'd be hard-pressed to find knowledge-based roles that don't require understanding data.
The Definitive Guide!
idea_plus_plus Thank you!
Nice
Really thanks
Hi Raj. Once a model has been built and deployed, its performance needs to be monitored, as does the business environment in which it operates. Events like a new piece of insurance legislation can fundamentally alter the parameters against which the model was originally developed. Is there a role in the Data Science arena that covers this kind of responsibility? Or do you see it being an operational responsibility?
Hi PG, Great question.
I've found that the operational people are often not so familiar with the model, other than knowing it as a black box. So while they might be monitoring the performance of the system/model(s), it's often left to the data science people to adjust it with new data or new context as you mention above, if the model performance 'drifts.'
That's sensible Raj. It feels to me like some collaberation is required here. Business strategists and managers need to be aware that the Data Science group is now part of the bigger team, and so needs to be kept informed about strategic developments that might impact production models. A joint impact review exercise is used to transfer knowledge to the Data Science group who then pick up the model adjustment work as you describe. Business Architects are well-positioned to encourage this information flow.
hello Sir,
Can one single person play the role of a data engineer in all these processes? Is it necessary to know the skills of all roles?
Thank you
Typically not. Choose the role you'd like to play and focus to build your strengths and skills on that. As you learn more, you'll broaden your skills
Good
Thanks Joel
lol he thinks google and amazon research new machine learning algorithms