Distributed Data Show Episode 80
In this episode Jeff talks with Max Melnick about how he got into analytics consulting with Deloitte (no, he's not an accountant), and how the Mission Graph capability Deloitte has built on top of DataStax Enterprise helps analysts leverage complex networks to detect financial fraud, terrorism, and even supply chain vulnerabilities.
0:15 -You told us you want to hear about use cases, so here we go!
0:58 - Getting to know Max - Virginia native, TensorFlow committer, Analytics at Deloitte
2:35 - The problem space for Mission Graph - identifying high-risk actors in networks aka "bad guys" to help analysts be more effective
3:53 - Mission Graph - solving not only the data problem of high volume, but the operational problems of connecting/correlating across data sets
5:35 - Mission Graph is a self-service platform for interactive network exploration and analysis. With current systems, most analyst time is spent on data engineering tasks. Mission Graph is trying to fix this.
7:58 - The technology stack includes Cassandra, DataStax Search, DataStax Graph. Lessons learned include: 1) avoiding network-based storage and doing regular health checks.
9:48 - 2) When onboarding new team members, give them initial tasks that correspond to their skill level.
11:17 - 3) When using Graph, use the DSE GraphFrames API for large volume data loading. Use Spark GraphFrames to take advantage of algorithms page rank, motif finding, etc.
13:28 - Wrapping up
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