Webinar: Transforming Customer Experience Through an Always-On Data Platform

Transforming Customer Experience Through Database ArchitectureFebruary 2, 2017Mike Gualtieri, Vice President & Principal Analyst, Forrester ResearchRajay Rai, Head of Digital Engineering, Macquarie Bank

Speaker Bios

© DataStax, All Rights Reserved. 2

Mike GualtieriVP and Principal Analyst

Forrester Research

Rajay RaiHead of Digital Engineering

Macquarie Bank

What new business priorities drive the

need for faster analytics

architectures?

© 2015 Forrester Research, Inc. Reproduction Prohibited 4

Better leverage big data and analytics in business decision-making

Create a comprehensive strategy for addressing digital technologies like mobile, social & smart products

Create a comprehensive digital marketing strategy

Better comply with regulations and requirements

Improve differentiation in the market

Increase influence and brand reach in the market

Address rising customer expectations

Improve our ability to innovate

Reduce costs

Improve our products /services

Improve the experience of our customers

0% 10% 20% 30% 40% 50% 60% 70% 80%

52%

53%

53%

54%

58%

64%

64%

65%

66%

73%

75%

› Base: 3,005 global data and analytics decision-makers

› Source: Global Business Technographics Data And Analytics Online Survey, 2015

Customer Experience and Product Innovation are Top Priorities

Customer Experience Must:

• Learn individual customer characteristics and behaviors

• Detect customer needs and desires in real-time

• Adapt applications to serve an individual customer

About Macquarie – Our Global Footprint

More than 14,300 staff in over 28 countries

EMEAStaff: 1,508

AsiaStaff: 3,599

Australia1

Staff: 6,676Americas

Staff: 2,589

EuropeAmsterdamDublinFrankfurtGenevaGlasgowLondonLuxembourg

MunichParisViennaZurich

South AfricaCape TownJohannesburg

Middle EastAbu DhabiDubai

New ZealandAucklandChristchurchWellington

Latin AmericaMexico CityRibeirao PretoSao Paulo

USAAustin

BostonChicagoDenverHouston

Los Angeles

CanadaCalgaryMontrealTorontoVancouver

ManilaMumbaiSeoulShanghaiSingaporeTaipeiTokyo

AsiaBangkokBeijingGurgaonHong KongHsin-ChuJakartaKuala Lumpur

NashvilleNew YorkPhiladelphiaSan DiegoSan FranciscoSan Jose

Australia AdelaideAlburyBrisbaneCanberraGold CoastManlyMelbourneNewcastlePerthSydney

Boca Raton

JacksonvilleMadrid

A new wayof work

ClientExperience

ITTransformationPartners

We always exceedclient expectations

We have an agileway of work, led by

client needs

Strategic partners arekey actors in ourdigital strategy

Service-driven IT,instead of systems

oriented IT

Our Digital Transformation Changes Our Focus

Product –> Client

Main Drivers of Our Digital Transformation

Automatic categorisation

Natural language search

Delivering Intelligent Assistance

Why do traditional analytical

architectures fail us?

10© 2016 Forrester Research, Inc. Reproduction Prohibited

Quick turnaround on customer requests

More data availability

Expanded access to more business users (i.e., self-service)

Low cost

Advanced analytics capabilities (e.g. predictive. prescriptive, streaming)

Faster performance (time to value)

11%

11%

12%

16%

24%

25%

Base: 100 data science and data analytics leaders at enterprises within the USSource: A commissioned study conducted by Forrester Consulting, April 2016

Faster Time to Value and Advanced Analytics is Most Important to Business

“As you look to improve your data processing and analytics capabilities, what aspect of the implementation is most important to your business? Please select one.”

Real-time Insights

Strategic Insights

Operational Insights

Performance Insights

Tim

e to

Act

Perishability

Sub-second to seconds

Seconds to hours

Hours to weeks

Weeks to Months

Sub-second to seconds

Seconds to hours

Hours to weeks

Weeks to Months

Enterprises must discover and act on a full range of perishable insights to get value from data

Most Analytics Operations Are Too Slow

Bus

ines

s Va

lue

Time To Action

Data originated

Analytics performed

Insights gleaned

Action taken

Outdated insights

Impotent or harmful actions

Pos

itive

Neg

ativ

e

Decision made

Poor decision

Real-time and batch analytics must happen faster

Real-time Insights

Strategic Insights

Operational Insights

Performance Insights

Sub-second to seconds

Seconds to hours

Days to weeks

Weeks to years

Sub-second to seconds

Seconds to hours

Hours to weeks

Weeks to years

Real-time analytics

Batch analytics

Tim

e to

Act

Perishability

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General Purpose Database

• Technologies• Apache Cassandra™: Continuous availability for mixed workloads • Apache Kafka™: manage real-time feeds• Search• Apache Storm™: real-time processing

• How to integrate and manage these disparate pieces?

Macquarie’s Preliminary Investigation

16© DataStax, All Rights Reserved.

We selected a data platformAlways-on data platform built on the industry’s best version of Apache Cassandra™,

with integration for Search, Analytics, Graph, and Operations Management

What is the new architectural

imperative to speed insights-to-action?

Scale to handle any volume of data.

Process and analyze blazingly fast.

ESB / Product Services

Core Banking Cash Management WealthCards Mortgages

Digital Services (Micro Services)High

Cadence

SlowCadence

Smart Data Store

API Gateway

Bimodal Architecture

Prediction

Full-Text SearchFacets based search Real Time SearchSynonymSpatial Engine

Read Optimized ModelMetaData TransactionsCounters for Category

Batch Analytics

Solr

Cassandra

Interactive Mobile Statistical Analysis/Reporting

Product Services

Spark

Channel/Data Services

PersonalizationReal

Tim

e Da

ta In

gest

ion

& Pr

oces

sing

Streaming Data Events, Replicate Data

Tables from Transactional Applications

Transactional Systems, Databases,Flat Files, Batch Data Feeds

Bulk Data Ingestion CoreBanking

LocationPersonalization

Push Notification

Alerts and Notification

Logs and Activities

StatisticalCore

Banking

CEPStreaming IFTTT

Customer Experience Platform

Micros Services : Scala (Spray), NodeJs, Spring Boot

Replication

Site 2Search

Site 2Analytics

Site 1Search

Site 1Analytics

Channel Services/API

Micros Services : Scala (Spray), NodeJs, Spring Boot

Topology of our Architecture

How are you using DSE to become the world’s top digital

bank?

What business or customer experience outcomes were you

able to achieve?

What’s next for your digital / CX

transformation?

Q&A

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Contacts & ResourcesGuest Speakers• Mike Gualtieri, Vice President & Principal Analyst, Forrester Bank

• LinkedIn: https://www.linkedin.com/in/mgualtieri | Twitter: @mgualtieri

• Rajay Rai, Head of Digital Engineering, Macquarie Bank• LinkedIn: https://au.linkedin.com/in/rajay-rai-742a082 | Twitter: @rajayrai

DataStax• Andrew Lampitt, Senior Director of Product Marketing @ DataStax

• Email: andrew.lampitt@datastax.com • LinkedIn: https://www.linkedin.com/in/alampitt | Twitter: @AndrewLampitt

Proofpoint

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