Grooming Data Modelers
Sue Geuens, DAMA International
Very often people fall into the data world – almost by accident. But, once in, how on earth do we as a “newbie” Data Management professional move forward? And what do our employers need to do to make sure that we actually fit into the new world we are navigating?Sue has spent more than 20 years now in Data Management, is a self-confessed “dataholic”, totally loves what she does and is always more than willing to share her knowledge and expertise with anyone who asks.In this session you will learn:
- What are the requirements for being a “good” data modeller?What would make you a “bad” data modeller?
- How can we change what we are doing and get on the right track?
- How do we leverage off what other DM professionals are doing?
- What are the skills and expertise that we feel we need and how are we going to acquire them if we don’t already have them?
Sue Geuens started in Data Management during 1996 when she was handed a disk with a list of builders on it and told they were hers to manage. Sue mentions this as fate taking over and providing her with what she was “meant to do”. Various data roles later, her clients numbered 3 of the top 4 banking institutions in SA, a number of telco’s and various pension funds, insurance companies and health organisations. Sue was the initial designer of data quality matching algorithms for an SA built Data Quality and Matching tool (Plasma Mind).
This experience stood her in good stead as ion until the end of 2015. As current President of DAMA International, she has bee active in supporting the recognition of data management and the range of expertise required by an information professional. she slowly but surely climbed the ladder in Southern Africa to become the first CDMP in the country. Sue worked tirelessly on starting up DAMA SA holding the Inaugural meeting in February of 2009 as Chapter President and held the position until the end of 2015. As current President of DAMA International, she has bee active in supporting the recognition of data management and the range of expertise required by an information professional.