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Winfried Adalbert Etzel - DAMA Norway에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Winfried Adalbert Etzel - DAMA Norway 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
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#17 - Return of Investment for Data Quality (Nor)

29:42
 
공유
 

Manage episode 324542798 series 2940030
Winfried Adalbert Etzel - DAMA Norway에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Winfried Adalbert Etzel - DAMA Norway 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

Can you put a value on quality data? Definitely! But how?
Who better to ask than Kristin Otter Rønnevig and Espen Hjelmeland? They both dedicated their master thesis to explore this topic with really interesting results. Their thesis "An Investment Perspective on Data Quality in Data Usage" asks "How can an organization optimize its investments in data quality?"
To answer the question Kristin and Espen posed three Research Questions:

  1. What are the main drivers for willingsness to pay for data quality?
  2. What part of data quality aspects should one invest in to maximize opportunities and minimize risk?
  3. How can the quality of data be improved, and what are the costs?

Here are some of their key observations, I found particularly interesting:

  • Increasing confidence in data in order to enhance company operations is one of the
    motivations for willingness to pay for data quality.
  • A greater level of knowledge in data quality gives a higher willingness to pay for data quality.
  • Demonstrating to the customer how quality improvements may enhance profit at each step
    of the value chain contributes to the willingness to pay for data quality.
  • Prioritizing improvements are based on the time and cost of the particular improvement. A way to reverse-engineer the impact of various improvements
    can help to identify how to improve the quality.
  • It is critical to invest in a professional, highly skilled team environment to succeed
    in data quality investments.
  • To cope with data quality, it is necessary to invest in security.
  • To know whether the organization is investing in data quality optimally, it will need a deep understanding of the business and experience with it.
  continue reading

55 에피소드

Artwork
icon공유
 
Manage episode 324542798 series 2940030
Winfried Adalbert Etzel - DAMA Norway에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Winfried Adalbert Etzel - DAMA Norway 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

Can you put a value on quality data? Definitely! But how?
Who better to ask than Kristin Otter Rønnevig and Espen Hjelmeland? They both dedicated their master thesis to explore this topic with really interesting results. Their thesis "An Investment Perspective on Data Quality in Data Usage" asks "How can an organization optimize its investments in data quality?"
To answer the question Kristin and Espen posed three Research Questions:

  1. What are the main drivers for willingsness to pay for data quality?
  2. What part of data quality aspects should one invest in to maximize opportunities and minimize risk?
  3. How can the quality of data be improved, and what are the costs?

Here are some of their key observations, I found particularly interesting:

  • Increasing confidence in data in order to enhance company operations is one of the
    motivations for willingness to pay for data quality.
  • A greater level of knowledge in data quality gives a higher willingness to pay for data quality.
  • Demonstrating to the customer how quality improvements may enhance profit at each step
    of the value chain contributes to the willingness to pay for data quality.
  • Prioritizing improvements are based on the time and cost of the particular improvement. A way to reverse-engineer the impact of various improvements
    can help to identify how to improve the quality.
  • It is critical to invest in a professional, highly skilled team environment to succeed
    in data quality investments.
  • To cope with data quality, it is necessary to invest in security.
  • To know whether the organization is investing in data quality optimally, it will need a deep understanding of the business and experience with it.
  continue reading

55 에피소드

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