What key skills or attributes do you consider have contributed to your success in your current role?
One of my most important skills is my visionary leadership. I have a clear vision of what I want to achieve with the Chief Data Officer & Information Quality (CDOIQ) Symposium now on its 17th year. We also have regional CDOIQ Symposium as follows:
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CDOIQ-LATAM in Brazil
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CDOIQ-APAC in Singapore
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CDOIQ-USA in Boston, MA
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CDOIQ-Europe in Switzerland
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CDOIQ-Nordic in Finland
I can communicate my vision effectively to my team and inspire and motivate them to work towards achieving it. Another key attribute that I possess is strategic thinking. I am able to see the big picture and think long-term, anticipating potential challenges and opportunities and developing strategies to address them. I am also able to adapt to changing circumstances and make necessary adjustments to stay on course. My effective communication skills have also been crucial to my success. I can build strong relationships with my team, clients and stakeholders through clear and articulate communication. I can provide guidance and feedback to my team and clearly articulate my vision and goals to stakeholders.
Finally, my mission-vision is to establish a CDO role in every organization with budget, authority and resources.
What level of data maturity do you typically encounter across your client base and what tends to hold this back?
In general, most of them are at different levels of data maturity. Some may be in the early stages of data collection and management, while others may have well-established data governance frameworks and advanced analytics capabilities.
However, it is not uncommon for organizations to have varying levels of data maturity across different departments or business units. Some common factors that can hold back data maturity include a lack of clear data governance policies, inadequate data infrastructure, insufficient data literacy and skills among employees and resistance to change and adoption of new technologies and practices. Other factors that can impact data maturity levels include a lack of leadership support or investment in data initiatives, poor data quality and siloed data within different systems and departments.
What trends are you seeing in terms of the data and analytics resources your clients are demanding from you?
While somewhat separately developed, the terms ’data fabric’ and ’data mesh’ are occasionally used interchangeably or the focus of conversations about concepts that conflict with one another. An emerging technological pattern that employs metadata to automate data administration tasks is the main force behind the ’data fabric’ data management design, which is a dynamic data management architecture.
