That was an especially good explanation dear Nicola! And yes, I smiled several times - you are so right!
@CrisMassena17 күн бұрын
Thanks for sharing!!! You both are amazing!
@lebenemawudor913Ай бұрын
Great answer
@paramt6067Ай бұрын
Hi, One question out of topic, how do you create a generic DG policy for a project where all the policy will not be relevant
@meriemhaha2704Ай бұрын
Great video thanks❤
@ladeoshunremi8084Ай бұрын
I agree, Data Governance first
@enwezornzegwu2494Ай бұрын
Great practical advice as ever!
@RehanAli-k9i2 ай бұрын
Halp
@GalaxyGax2 ай бұрын
How are Data Custodians different from Technical Stewards?
@jackieo71132 ай бұрын
Hi there, great info.. fyi, the 1st two links aren't active
@tangooo61713 ай бұрын
Great
@adammorra38133 ай бұрын
Very great video and a foundational topic.
@sindixx3 ай бұрын
Interesting
@chriseddy19823 ай бұрын
I would like to the stakeholders who can log DQ issues. I have a concern on how to prioritize DQ issues. How do I mitigate against the logging process being overwhelming. How do we ensure that only top priority DQ issues are raised.
@TheDataGovernanceCoach4 ай бұрын
See the following link to one of my previous videos for some guidance on how to implement a Data Governance framework: kzbin.info/www/bejne/rYbCn4iHfb-Ioqc
@CaponacFe4 ай бұрын
Thanks Nicola
@carlmerritt43554 ай бұрын
Business are often surprised when I tell them IT doesn't own the data - it's a business asset. It's the business which will make decisions off the back of well governed data - not IT.
@TheDataGovernanceCoach4 ай бұрын
Yes, it's amazing how many think it is IT's responsibility!
@adammorra38134 ай бұрын
Very good video, simple but powerful. Especially for people starting their journey.
@TheDataGovernanceCoach4 ай бұрын
Glad you enjoyed it!
@TheDataGovernanceCoach4 ай бұрын
Lear more with my top tips here: docs.google.com/document/d/1G9YPU3vsvYq0sLYkSRYbigUZAt1z-ucoS0AcnYnD6sY/edit
@adammorra38135 ай бұрын
You are so brilliant, thank you for your hard work.
@adammorra38135 ай бұрын
Really great point and good anaology!
@TheDataGovernanceCoach5 ай бұрын
This is the link to my other video explaining what a Data Governance policy is! kzbin.info/www/bejne/pnecfXSuYtCBa6s
@chqaisar-bw9mp5 ай бұрын
0:24❤❤❤❤
@andrechristensen44886 ай бұрын
Keep it up dude!!! I think you will be interested in smzeus!
@annaquer996 ай бұрын
But how you define who is the owner in such kind of data? there are any questions we could answer to get the right person to be responsible for? thanks!
@archanapattanaik87136 ай бұрын
Thank you Nicola
@TheDataGovernanceCoach7 ай бұрын
Link to the original video is here! kzbin.info/www/bejne/rYbCn4iHfb-Ioqc
Some more videos relating to Data Owners can be found on the following links. Enjoy! kzbin.infoplsVC9iSFRY kzbin.infod3HRWf0o_uQ
@tangooo61719 ай бұрын
I did everything engineering and managing very hard 😢
@tangooo61719 ай бұрын
So what can you do if you are the creator , and need full access ?
@colinmacguire9 ай бұрын
Thanks for the video, Nicola. Why would a Data Product Owner be different to a Data Owner if the product derived by the "Data Product Owner" comes from data owned by Data Owners? Should the data governance committee rather not decide on the rules of use for the Data Product, rather than leaving this for the "Data Product Owner" to do, and in so doing, introducing what seems to me to be a conflicting role?
@tangooo61719 ай бұрын
Awesome
@TheDataGovernanceCoach9 ай бұрын
Thank you!
@AundKx Жыл бұрын
@TheDataGovernanceCoach I'm afraid I have a silly question, sorry. Where would the data governance fit if I were to draw a timeline for the data engineering process? Would it be before the engineers start data ingestion or somewhere else along the pipeline? BTW. That was the best explanation I've ever heard. Thanks.
@sainthubertbernard Жыл бұрын
Nicola, we ended up with the option of having two data owners. Only thing is we called them as Primary Data Owner and Secondary Data Owner. The criteria is the function who produces the data with maximum number of critical attributes is defined as the Primary Owner and the other function is tagged as the secondary data owner. From a RACI perspective, the primary owner has the accountability of that complete data entity and the secondary owner has the responsibility on the critical data attributes that he owns in that data entity.
@rockyball8718 Жыл бұрын
👀 'Promo SM'
@SteveCrosson-Smith Жыл бұрын
I completely agree Nicola. I work with companies to help formulate data strategies and governance is inevitably one of the key themes that comes out strongly - even when the company had not expected it to. To me, governance is a key enabling pillar of a data strategy.
@vindolanda6974 Жыл бұрын
Data Mesh is not a technology. Also, you don't mention the concept of 'Federated Computational Governance'. I'm still trying to work out how it relates to traditional enterprise data governance roles, organisations and operating models.
@user-mm1ch7vw6h Жыл бұрын
Really useful, thank you. Maybe a next video or blog could be giving a real world example of HOW Data Governance supports each of the other data management disciplines on the wheel.
@TheDataGovernanceCoach Жыл бұрын
Great suggestion! Thank you!
@alexandresantana7105 Жыл бұрын
I completely agree with the argument. In fact we expect that within our organization especially those involved in data projects have some level of data literacy. In practice what often happens is that they do not have the level that is intended and that is where we enter, of course, in the scope of fluency.
@linda-jograham9669 Жыл бұрын
This has been my argument for years, but I could not think of a better word than Literacy. Thank you for articulating my minds thoughts!
@nicusky Жыл бұрын
What is a big or small it company in this context ?
@stevechambers1060 Жыл бұрын
Nice short clip!
@user-fe6wx6ol8b Жыл бұрын
Good points Nicola. I would point out however that the use-case for data lineage for the data governance team is different from the use-case for the data engineering team. They need lineage for different purposes. The governance related need is primarily to follow the path to know where their data comes from, and perhaps something about how the transformations may be impacting the final output on the reporting layer. On the other hand, the data developers and engineers use lineage to be sure that they know what will be impacted by the changes they make to the data flows. As such, the technical lineage you described as being far to granular will be difficult for a business users trying to get the basics from the lineage map, but critical to the engineers to ensure that the data flows as designed, and thereby ensuring top data quality. With all that said, a good data lineage solution provides both ways to consume the information, and in a format that is digestible for the business users, while technically sound enough for the data engineers. Of course, this is coming from a vendor of Data Lineage Automation (Octopai.com), but we also have a data catalog that is designed for the data governance types too. As such, our approach is to provide both perspectives in a way that will not only be easily understood, but also double as a way for the two stakeholders (IT and Business) to collaborate around the use of the data elements in the landscape. Care to learn more? Ping us on octopai.com.
@Laura_W_376 Жыл бұрын
Thank you for the break-down.
@AI-dz2zd Жыл бұрын
One of the issues of Data Governance today is really the complete disconnect from the reality. The sole fact that you find Data Engineering "trendy", on its own is a statement of complete lack of understanding of how "data" works. Good luck on your high throne of delusion.
@phrumdata Жыл бұрын
Glad to see this topic covered. I agree that training an ML model on datasets with data quality issues is a poor idea. If an ML model was trained on high quality datasets it will be more effective of course. Since general AI doesn't exist yet we will need human input, it's not out of this world for a data governance application to analyze a dataset and suggest data quality rules. I'm hoping the data governance applications begin to implement something like this feature, it would reduce the amount of human involvement at least. There could even be an ML model for specific dataset contents, for example a database field "SSN" could be read and identified as a social security field. The model would then suggest data quality rules and ask for human input, this is taking use of the data labeling concept.
@BarryG-hv8nb Жыл бұрын
Love this analogy !!!😃
@TheDataGovernanceCoach Жыл бұрын
Thank you!
@loreweaver33 Жыл бұрын
Great video, as always. When our governance office took on access management, it was with our security team and our goal was to engage and help automate and audit access with our data owners, so it was a natural fit. Data Governance always seems to be the ultimate collaboration group!
@SteveCrosson-Smith Жыл бұрын
Spot on, Nicola. Statistical Process Control (SPC) is an example of using AI to look for data that is outside of a statistical norm and its real power is to augment human involvement rather than replace it. It simply isn't practical for humans to adaptively monitor the plethora of data flowing around a company, especially as the window of opportunity to act upon insights derived from it is forever narrowing.