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You can stop cleaning your data now

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Manage episode 403561766 series 3357328
Content provided by Collibra. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Collibra or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

We all know that every bit of an organization’s data ought to be treated equal, right? Well, in a world where clean data is often the status quo, Julie Fawdington, Senior Director PMO at Hewlett Packard Enterprises, invites us to ask the question, how clean is clean enough?

Drawing on her extensive experience in data transformation, Julie’s take on data quality suggests the need for data quality differentiation. As she puts it, the stuff in her pet’s water bowl isn’t the same as what’s in her water bottle. But does this idea that not all data requires the same level of cleanliness really upend conventional wisdom? Or does it simply provide a more nuanced understanding of how to efficiently manage data in today's fast-paced business environment?

Three reasons you should listen to this episode:

1. Redefining data standards. Discover Julie's unique approach to data quality and how it can revolutionize your data management practices.

2. Empowering data stewards. Examine the role of data custodians and stewards in driving business processes and effectively managing data quality and governance.

3. Leadership's role in data management. Learn practical steps for how leaders can promote data quality and management within their organizations.

Resources


Enjoyed this Episode?

Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.

Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.

  continue reading

35 episodes

Artwork
iconShare
 
Manage episode 403561766 series 3357328
Content provided by Collibra. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Collibra or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

We all know that every bit of an organization’s data ought to be treated equal, right? Well, in a world where clean data is often the status quo, Julie Fawdington, Senior Director PMO at Hewlett Packard Enterprises, invites us to ask the question, how clean is clean enough?

Drawing on her extensive experience in data transformation, Julie’s take on data quality suggests the need for data quality differentiation. As she puts it, the stuff in her pet’s water bowl isn’t the same as what’s in her water bottle. But does this idea that not all data requires the same level of cleanliness really upend conventional wisdom? Or does it simply provide a more nuanced understanding of how to efficiently manage data in today's fast-paced business environment?

Three reasons you should listen to this episode:

1. Redefining data standards. Discover Julie's unique approach to data quality and how it can revolutionize your data management practices.

2. Empowering data stewards. Examine the role of data custodians and stewards in driving business processes and effectively managing data quality and governance.

3. Leadership's role in data management. Learn practical steps for how leaders can promote data quality and management within their organizations.

Resources


Enjoyed this Episode?

Be sure to follow us so you never miss an update. You can leave us a review on Apple or Spotify, and share it with your friends and colleagues to help others learn more about the importance of a data-first digital transformation approach.

Have questions? You can connect with us on LinkedIn. For more updates, please visit our website.

  continue reading

35 episodes

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