ANZ Presentation: GraphSummit Melbourne 2024
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The document discusses modern data management strategies aimed at achieving AI-enabled systems within large organizations, focusing on the importance of metadata for trust and understanding. It emphasizes the need for connected data to drive value and scalability, moving away from siloed and static data management approaches. The adoption of a data fabric design and innovative tools, such as knowledge graphs and AI, are presented as key components to enhance data maturity and facilitate insights.
ANZ Presentation: GraphSummit Melbourne 2024
- 1. MODERN DATA MANAGEMENT AT SCALE JOURNEY TO AI ENABLED DATA Data Management Office, ANZ Australia Graph Summit Melbourne 2024 Classification: Public
- 2. METADATA ENABLES TRUST & UNDERSTANDING Untrusted Incomplete + Metadata TRUST! + Lineage
- 3. THE COMPLEX DATA LANDSCAPE LARGE ORGANISATIONS FACE TODAY Culture Volume Modernisation efforts coexisting with legacy Regulatory landscape
- 4. DATA MANAGEMENT: MAPPING THE JOURNEY TO MATURITY Organised Data Catalogued Data Managed Data Unorganised Data Intelligent Data Low data maturity Foundational data maturity Modern data maturity Transformational data maturity Innovative data maturity + common language = + consistent = + context = + structure =
- 5. MODERN DATA MANAGEMENT; EMPOWERING A DATA-DRIVEN FUTURE Traditional Data Management Limited Scalability Dashboards Batch Static & Controlled Only Reg Data Siloed Data Designed to Scale Knowledge Graphs Real-time Agile, flexible Data Innovation AI-ready Data Modern Data Management Data Capabilities Defense Offense
- 6. OUR APPROACH TO DRIVE MODERN DATA MANAGEMENT Culture • Purpose Led • Invest in people & skills • Build a foundation Focus • Connecting our data • Bold, Modern but with empathy • Engagement = Adoption Capabilities • Investment in purpose-build capabilities: • Metadata Management • Semantic Modelling • Knowledge graph / AI Discovery
- 7. CONNECTED DATA FUELS VALUE, DRIVES SCALE Siloed Data is: • Incomplete • Expensive Connected Data is: • Contextual • Value-driven Data in Cloud Data in Lakes Data in Staging Areas Data in Streams Data in Warehouses
- 8. DATA FABRIC: AN EMERGING DATA MANAGEMENT DESIGN TO ENABLE CONNECTED & AI READY DATA External Reference Models Enterprise Data Taxonomy Semantic Rules Data Quality Rules Conceptual Data Model Business Terms & Context Business Rules Reference Data Metadata Catalogues Data Products Metadata Context Mapping Knowledge Graph GenAI Semantics, Consistency & Innovation Data Fabric
- 9. BRINGING THIS TO LIFE. A STORY AND AN EXAMPLE Data Lineage can be time & resource consuming. We’re investing in Data Fabric, Knowledge Graph & Gen AI to innovate & experiment. As a result, we are now able to semantically connect data, visualise and generate insights without needing deep technical knowledge every time. Let’s take a look at one of the capabilities that we are working on.
- 10. CONNECTED DATA LINEAGE WITH AI Data Sources Staging Area Data Lakes on Cloud Data Lakes on Prem Data Users Data Lineage RAG (Retrieval-Augmented) Architecture Chatbot Enabled 1. Ask the right questions, using the Chatbot 2. Access the correct Data Lineage 3. Enable tracking of the correct information Converted into Knowledge Graph
- 11. DEMO
- 12. RECAP - METADATA MATTERS – DATA MUST HAVE CONTEXT TO BE USEFUL 8 sliced Rosacea fruit of the Prunus Persica suspended in a solution of polysaccharides from Barbados and H2O in a Zinc-Alloy container and Bishphenol-A An indication of the Producer and Quality Regulatory required information (ingredients and nutritional values) Easy to identify Provenance (Lineage) Instructions (how to use) Serving suggestions (may go well with) Best Before Date (freshness) It could be anything No Metadata Technical Metadata May be true but how it is useful? Business & Technical Metadata Labelled to be found, understood & used
- 14. THANK YOU