13 June 2017© COPYRIGHT MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.

The Data-Hub Journey at Erie InsuranceBrian Novacek, Erie Insurance

Derek Laufenberg, MarkLogic

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Operational Dataflow ChallengesWho are my customers? ▪What services might they need?

How do I keep them? ▪ What are the business risks? ▪ How valuable is…?

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60% OF THE

Of data warehouse projects is on ETL

COSTDevoted to just “keep-the-lights-on” activities

In security budgets, while IT budgets overall remain flat

72%INCREASE50 % OF

BUDGETS

DATA INTEGRATION DATA SECURITY MANAGEABILITY

Today’s Data Management Challenges

Erie Insurance

• Fortune 500 Company located in Erie Pennsylvania• A+ (Superior) rated by A.M. Best Company• Over 5,000 employees and 12,000 independent agents• 10th largest homeowner insurer in United States• 12th largest automobile insurer in United States• 15th largest property/casualty insurer in United States

To provide our Policyholders with as near perfect protection, as near perfect service, as is humanly

possible, and to do so at the lowest possible cost.

What is our mission?

Erie’s Challenges

• Application Data Silos• Shadow IT Systems• Complex Workflow & Integration Processes• Data Mastering Challenges• Aging Mainframe Applications & Hardware

– Need a 360 view, or golden record

Erie’s Business Need

• High Speed and Open/Extensible Delivery Platform• Cross Lines Integration & Data Mastering• Data Integrity with Security

Erie’s Technical Goals

• Improve Application Delivery Times• Utilize Agile Processes• One Simple Goal

• Turn data into information as fast as possible• Golden record with 360 degree view

• Researched Platforms and Options

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Erie’s Search

Erie’s Search

• NoSQL & Document Databases üFlexibilityüScalability

• Needed Security, Transactions, & BI • Support Enterprise Operations

LearnedofMarkLogicandData-HubPattern

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Fixing the PictureA NEW ENTERPRISE INTEGRATION PATTERN

§ Traditional integration technologies are people intensive

§ Copying the same data to support different needs is the norm because of rigid models

§ A flexible, scalable operational databaseis the foundation for a Data Centricapproach

§ Greater convergence between analysis and operations is critically important

§ The new Enterprise Pattern is the Operational Data Hub

Quotes

Ratings& Risk

Multiple CRMs

Claims

Billing

3rd Party DataAgency

Policy

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Definition 1.2Operational Data Hub (ODH)

An authoritative data repository for cross-functional operationsthat harmonizes line-of-business data into a canonical forms on an as-needed basis.

It serves as a multi-subject, multi-model, contextual, real-time, integrated and data-centric enterprise interchange in support of enterprise operations and analysis/discovery throughout the data lifecycle.

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MarkLogic ODH Pattern

MESSAGEBUS

RDBMS

CONTENTFEED

ING

EST

ANALYTICALAPPS

OPERATIONAL APPS

DOWNSTREAMSYSTEMS

SERV

E

STAGING(RAW DATA AS IS)

FINAL(HARMONIZED, INDEXED DATA)

SOURCE 1 DOCUMENTS

SOURCE 2 DOCUMENTS

SOURCE NDOCUMENTS

ENVELOPED DOCS (ENTITY 1)

ENVELOPED DOCS (ENTITY 2)

ENVELOPED DOCS (ENTITY N)

HA

RM

ON

IZE

INDEX, SEARCH, DISCOVERY, &

HARMONIZATION

INDEX, SEARCH,& SERVICES

f(x)

POC Overview

ObjectiveProve whether or not document data modeling and storage can improve flexibility and accelerate application development.Understand impacts when model changes occur.

Scope• “System of Record” use case• Day 1 ‘Add & Maintain

Individual Entity Data’ • Compare/contrast application

development with document models

Document Relational

RelativeAppliedTime

DocumentPOC

RelationalDB

POC Summary

Why MarkLogic• Enterprise grade –

– ACID Transactions– Backup – point in time restore – High Availability and Disaster Recovery– Security

• Flexible data model– easy to work with– fast search

• Scalability and real-time alerting• Approximate 4:1 improvement overall application delivery

Three Pillars for Success

Technology

Process People

Technology Change…

• Short story – it works!• Longer Story –

– Data Hub Pattern– Scalable, Enterprise– … you get the picture

Process Change…

• Make your process more agile• ETL becomes ELT• Data model as you go

– Load sources iteratively – Harmonize as applications require– No “big bang”

• Communicate – repeatedly

People Change…• Socialize the Technology

– Data Hub Pattern– Search & discovery– Incremental data modeling

• Expanding with the right projects– Match project to team’s skill level– Keep focused

• Leverage Your MarkLogic Sales Engineers– Email / WebEx Sessions– Onsite Office Hours

Becoming Self-Sufficient

• Select projects that match team’s skill level• Build a Center of Excellence

– Open minded architects and developers– Skilled in multiple API, languages– Track record of embracing new technology

• Leverage MarkLogic Consulting to augment your domain experts• MarkLogic University

Erie Today…

• We are building a Data-Hub using MarkLogic• We are doing it the MarkLogic way• Focused on new & improving processes• Leveraging acceleration while learning• Delivering Faster

Q & A