Episode Title : Defensive Versus Offensive Data Strategies
Data is never perfect. The key question for data practitioners should be ‘Is it good enough’ for the problem to be addressed’? Each analytics situation requires its own strategy with respect to the quality of data being fed and the time/cost it requires to incrementally improve the quality. Wendy Zhang had multiple hats at different companies as a data governance lead and data analytics lead. Wendy had the luxury of building a data governance team from scratch at Wells Fargo and now works with a consulting organization helping with data governance and analytics strategies.
Wendy also believes that organizations may need defensive or offensive strategies depending on their situation. If a financial organization needs to comply with regulatory mandates, a defensive strategy may be best. On the other hand, a mature data-capable organization will be best served with offensive strategies.
Youtube link: https://youtu.be/VSQN3ck4Gxo
02:00: Loan portfolio modeling includes credit modelling, data capability assessment and enterprise data governance.
03:00: Even within one organization, especially if it is a large organization, there will be multiple ‘data’ organizations with their own policies and structures.
07:00: Examining data governance standards towards a successful implementation of data analytics.
08:30 (Headliner): Data is never perfect. Key question is ‘Is it good enough’ for the particular challenge being addressed.
10:30: Wendy built a data governance team from scratch. Building a team groundup at Wellsfargo was a luxury but also a challenge of having to start from scratch.
12:00: Key best known methods for any data projects are: Gap analysis, Assessment, Organizational buy-in.
13:00: As an outsider coming in as a consultant, asking the right questions and providing a holistic and comprehensive assessment is valued by clients.
14:30: Defensive Vs Offensive data governance. Defensive strategies are aimed at being compliant. Offensive strategies are best suited for more data mature organizations.
16:30: Defensive is only a short term strategy. Offensive data governance allows a much more aggressive implementation of data analytics.
19:00 (Headliner): The talk about AI & ML. Every organization wants to do something about AI. The fundamental questions are ‘What do you want to do with AI’ and ‘Why? First assess the quality of data and skillsets and ask is ML needed?
Resources mentioned in this episode:
Podcast website: https://DataTransformersPodcast.Com
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