Difference between revisions of "Data Governance"
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| − | <youtube> | + | <youtube>HIaB5uiIs_0</youtube> |
| − | <b> | + | <b>What AI Means for the Future of Data Governance and Big Data |
| − | </b><br> | + | </b><br>Datum LLC Machine learning and artificial intelligence may well be the next frontier in business strategy. As companies across the globe race to understand how to operationalize AI concepts, vendors from every corner of technology are reacting by building (or claiming to have built) these capabilities. But before artificial intelligence can move past the hype, it must be measured from a business value and ROI standpoint and it must be trusted. This means it still requires data governance. |
| − | + | We conclude our series by covering the future of data governance and Big Data in an AI world. Everyone has heard how important data is to the training and learning process so the efficacy of the data will separate winners from the pack, but few have identified how to truly connect it to value. In this video we’ll touch on four key points to know before getting started with AI, including the single most important factor for success, the critical skills practitioners will need to develop (yes, humans are still part of the picture), and how to make AI truly scale in the enterprise. | |
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| − | <b> | + | <b>Enterprise Data Governance: Leveraging Knowledge Graph & AI in support of a data-driven organization |
| − | </b><br> | + | </b><br>As one of the largest financial institutions worldwide, JP Morgan is reliant on data to drive its day-to-day operations, against an ever evolving regulatory regime. Our global data landscape possesses particular challenges of effectively maintaining data governance and metadata management. The Data strategy at JP Morgan intends to: a) generate business value b) adhere to regulatory & compliance requirements c) reduce barriers to access d) democratize access to data In this talk, we show how JP Morgan leverages semantic technologies to drive the implementation of our data strategy. We demonstrate how we exploit knowledge graph capabilities to answer: 1) What Data do I need? 2) What Data do we have? 3) Where does my Data come from? 4) Where should my Data come from? 5) What Data should be shared most? Presentation by Aftab Iqbal, JP Morgan Information Architect, at Connected Data London 2019: |
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| − | <b> | + | <b>Data Governance and AI: New Dimensions in Privacy and Compliance | Dataiku & GigaOM |
| − | </b><br> | + | </b><br>This webinar walks through practicalities of governance in the age of AI, including governance “checkpoints” for data scientists; the relationship between data regulations, ethics, and AI; and making ML models compliant, both with government regulations and corporate policy. |
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Revision as of 09:36, 7 September 2020
Youtube search... ...Google search
- Case Studies
- AI Governance
- Enterprise Architecture (EA)
- Enterprise Portfolio Management (EPM)
- Architectures supporting machine learning
- Evaluation
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Access Sciences: Data Governance series
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