Discuss how IAG, Australia's leading Insurance company, uses Cassandra to change the way they integrate and leverage their data. First use case is in moving from Silos of data to enabling near real time analytics on critical digital application data leveraging kafka for data flows to Cassandra. Then leveraging Solr and Spark nodes to enable real time search and analytics. Second use case is in collecting new telemetry and telematics data to enable real time feedback to customers that initially shows 7-20% fuel savings for gas vehicles. This will also help customers to avoid heavy accident risk areas of cities during peak times and eventually suggest alternate routes and commute timing to reduce risk. About the Speaker Eddie Satterly Co-Founder, DataNexus Eddie has served in a variety of roles including developer, engineer, architect and CTO over his 27+ year career. At DataNexus he is building a new big data application. Previously he was CTO of the Emerging Technologies at CSC running product portfolio and R&D teams in: Cyber, Analytics, Cloud, Mobile & IoT. Prior in CTO Office at Splunk where he presented at events and set data strategy. Prior he revolutionized how Expedia delivers service to improve user experience using Cassandra. MVP

1. Eddie Satterly
CTO & Co-Founder DataNexus
@eddie_satterly
Real World Cassandra

2. 1 Who is IAG
2 Single Customer View
3 Telematics
4 Why Cassandra
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Insurance Leader
IAG is a group of top insurance brands
across Asia and ANZ region
Whether you are a customer, partner,
employee, shareholder or part of the
communities IAG serves across Australia,
New Zealand or Asia, IAG exists to ‘make
your world a safer place’.
The Group’s Vision is: To be Asia Pacific's
most loved, most inventive and most
successful insurer.

4. Data Challenge #1
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Problem Statement #1 – Customer View
As a group with a large number of brands and all with separate products
most with separate source systems it is very difficult to represent a
single customer in a useful way. There are over 130 internal source
systems with data and several external sources as well that make up
what IAG knows about customers, but no way to bring that data together.
The view to the right is a high level overview. This is a much harder problem to
solve than you might think and there has been more than 2 years of effort put into trying
various approaches using traditional data tools. All have failed

5. How to Solve for Customer View
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SQLfor21Attributes
+SystemKeys
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asters
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Allows Keys each to pull PII or Anon or Full Dataset
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Search UI

6. Data Challenge #2
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Problem Statement #2 – Telematics
Collection of massive amount of telemetry from devices in cars and homes provides
a very rich source of information to make critical Insurance decisions and get our
customers a better price and a better experience when they opt in to share. The initial
use case was simply to pull in data from a few vehicles and determine if customers
were interested in sharing that data to improve their insurance price in ANZ like they
are in the US. Since then there has also been a project undertaken to help save on
fuel and make drivers safer, in staying with IAG vision statement. On top of all this
there is also a current effort to work with customers on connected home platform to
price more accurately on home policies as well.

7. How to Solve for Telematics
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8. Why Cassandra
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Cassandra Solution Approach
All on Openstack Appliance
9 Nodes Cassandra with 3x800GB SSD
3 Nodes Solr with 3x800 SSD
All R3
2 node Kafka Broker for all data feeds
6 nodes Storm for processing and enrichment

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