This document discusses modernizing a company's data architecture using data virtualization to improve agile data delivery. It describes the company's current federated model and need to respond more quickly. The proposal is to implement a data virtualization layer to land data from various sources, create a conformed data warehouse, and provide a single data access point. This would virtualize data, reduce costs, improve flexibility and throughput, and accelerate change cycles compared to the current environment. A specific example of using this approach to enable daily and intra-day reporting from a new system is also described.

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Modernizing Data Architecture using Data Virtualization for Agile
Data Delivery
Dave Kay, Data Consultant
UKGI Data, Analytics and Architecture

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55,000Employees (approximately)
170+
Countries
USD 4.6 bn
Business operating profit

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The Zurich Group Operates a Federated Model for Data
Deliveries.
Group Function – Delivers Data Framework
Satellite Function – ZNA
Satellite Function – UKGI & UK Life
Satellite Function – Zurich Switzerland BU
Etc…

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Big change coming in Insurance – the ability to respond at pace is key to success.
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Learn about and build plans for:
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Driving toward a near future that
encompasses:
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With ambition for a longer term
where:
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SchedulingDataSources
ETLProcessing
SolutionDelivery
UserAccess

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Reduce
Cost
Flex
Resource
Raise
throughput
Accelerate
change
• Cost of change prohibitive to generating value from data
• Slower time to market inhibiting impact of good analytics
• Complexity of solution can cause delivery bottlenecks
• Bespoke coded solution requires unique resource to maintain

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Data
Landing
Conformed
Warehouse
Data Hub Interface
Layer
• Data landed into infrastructure from disparate sources
• Conformed enterprise data warehouse provides central storage
• Data hub providing single ‘user facing’ data source
• Simplified Interface layer landscape – single point of entry

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Business Need: Provide daily MI and intra-day
Operational Reporting for a community of business
analysts, salesmen, underwriters, managers and
actuarial staff – off the back of a brand new system.
• XML Source with over 13,000 elements, 10+ products
• XML Schema not available
• Data items and schema differ dramatically per
product type
• Fast pace of change

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• Subset of data ‘shredded’ via XSLT – immediately reduces scope
(250 items)
• SSIS transforms at multiple points generate maintenance difficulties
• Data effectively replicated multiple times
• Change Request process lengthy and expensive
• Specialist development skills required

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• XML made available into new DAA architecture for ingestion
• Denodo used as a virtual staging wrapper
• Views over XML representing core entities for reporting (Relational
View) virtualised in Denodo – cached to SQL Server
• Relational, Reporting and Analytical stores published as
consumable data sets via Denodo
• Two tier interface:
• Rapid interactive access to quickly changing data for ad-hoc
queries via Alteryx, JDBC, REST etc
• Stable, conformed relational marts virtualised & cached for
exploration, analysis and visualisation in Qlik etc

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DataSources
VirtualStaging
VirtualSemantic
AtomicWarehouse
VisualisationAnalytics

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Reduce
Cost
Flex
Resource
Raise
throughput
Accelerate
change
• Cost model reduced
• Significantly quicker time to market
• Greater throughput
• Resource pool expanded