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Wednesday, April 25, 2018 
12:00 PM - 01:00 PM
Blockchain technology brings a new paradigm to data processing. Having rapidly moved beyond its roots in crypto-currency transacting, it now offers exciting possibilities for sharing information between untrusted parties, without the necessity of a central operator. Acting as a potentially global scale multi-master distributed database, it also raises many questions and potential challenges for data management professionals. In this presentation, we’ll provide a brief overview of the technology and introduce some of the more common types of blockchain implementations. With that foundation, we will then address data modeling for blockchain applications: the criticality of semantics from a well-defined domain model and the use of bi-temporal event streams to provide an immutable source of record. We will then discuss the implications for data architectures, especially those pertaining to analytics, data warehousing, and data marts, and conclude with prescriptions for data management organizations.
- Blockchain – An overview of the latest data repository
- Data modeling for blockchain applications
- Blockchain implications for data architectures
- Recommendations for data management organizations
Ashton Thorogood is the lead Data Architect at AlphaPoint, a financial technology company that powers digital asset networks and provides institutions a Distributed Ledger Platform to digitize, trade, and manage any asset. With over 20 years of software development experience, he has held positions as Head of Enterprise Architecture, Lead Systems Architect, and Chief Data Architect at various firms, primarily within the Banking and Capital Markets industry. Ashton champions shared technical and business domain models and has led, mentored, and consulted teams across organizational boundaries, developing semantic models, enacting common data management practices, and designing and implementing enterprise data processing architectures. He has extensive experience in modeling for event-driven distributed systems, ensuring that data streams support both real-time reporting needs, as well as downstream analytics on large datasets. Ashton holds a BA in Political Science from The University of Pennsylvania and an MS in Information Systems from Drexel University.
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