HFS-不要被數(shù)據(jù)產(chǎn)業(yè)現(xiàn)代化所困擾（英）-2023

Don’tget

flummoxedbydataestate

modernization.Getfocused.AmajorNorth

American

bankusesCapgeminiand

Google

tomodernize

itsdataestate.Joel

Martin,Executive

ResearchLeaderElena

Christopher,

Chief

Research

Officer?

2023,

HFS

Research1Despite

decades

of

investment,

banking,

andfinancial

services

(BFS),

firms

struggle

withdelivering

data

to

where

it

can

be

used

mosteffectively

while

meeting

risk

and

regulatoryreporting

requirements.

These

struggles

haveled

to

a

shift

in

data

strategy

yielding

controlfrom

siloed

operations

to

a

data

managementmodel

utilizing

a

hybrid

cloud

architecture.complexity

of

data

and

the

need

to

manage

iteffectively,

it

is

advisable

to

think

less

about

thetechnology

components

and

more

about

thesources

of

the

data,

the

running

and

managingof

data

to

feed

multiple

data

requirements,

andthe

surfacing

of

that

data

through

applications,integrations,

and

analytics.Data

estate

complexity

can

lead

to

aA

shared

understanding

between

clientand

partner

of

what

a

data

estate

meansand

how

they

collaborate

is

crucial.technology

leader

wondering

where

theyshould

start

or

if

they

should

start

at

all.

Theleader’s

choices

are

typically

two-fold.

First,they

could

choose

an

iterative

approach

thatwill

yield

benefits

and

ensure

accurate

results,but

that

takes

time,

or

they

could

select

aprocess

that

develops

a

modern

datamanagement

foundation

that

treats

data

andinsights

as

separate

but

equally

important

dataassets.

Either

path

requires

a

firm

to

invest

inpartnerships

to

augment

resources,

addtechnology

capabilities,

and

address

financialregulatory,

governance,

and

securityA

data

estate

is

generally

defined

as

thecomponent

technology

making

upa

firm’s

dataarchitecture.

These

include

the

data

warehouseor

storage

architecture,

the

repository

for

rawdata

(e.g.,

data

lakes),

and

data

marts

(analyticstools,

software

applications,

and

reportingtools)

used

to

create

access

to

the

data.

Manylegacy

data

estates

run

on

mainframes,

arehoused

within

on-premises

data

centers,

andare

accessible

through

multiple

SQL

databasesand

business

intelligence

(BI)

tools

orrequirements.The

journey

to

better

data

is

never

complete.Even

as

we

wrote

this

paper,

many

firms

seekguidance

on

how

their

data

will

fulfill

thedemands

of

generative

AI

models

like

ChatGPTor

Google’s

Bard.

And

while

considering

thefuture

impact

of

these

large

language

models,it's

clear

that

those

firms

working

overtime

tomodernize

their

data

will

be

best

suited

to

gainan

advantage

from

these

game-changingsolutions.applications.As

an

organization

migrates

to

a

modern

dataestate,

many

of

these

solutions

are

re-architected

to

operate

in

a

hybrid

cloud

(a

mixof

private

and

public

cloud

and

on-premisessolutions)

or

100%

as

cloud-native

solutionsarchitecture.A

modern

estate

leveragestechnologies

like

NoSQL,a

cloud-based

datawarehouse

and

data

lake

houses,

and

analyticstools

like

Google’s

Big

Query.

Given

the?

2023,

HFS

Research2Set

yourself

upfor

success

by

adoptingpractical

steps

todata

estate

modernization.Modernizing

data

is

complex.

However,simplifying

the

discussion

around

aligning,accessing,

building,

running,

and

managingdata

to

drive

business

outcomes

is

crucial

togaining

support.

We

recommend

the

stepsshown

in

Exhibit

1

to

frame

the

journey

andensure

everyone,

from

the

CEO

to

the

businessanalyst,

understands

the

steps

to

take.Exhibit

1:

Fivecore

steps

tomodernizethedata

estate

todeliver

businessoutcomes12345Align

stakeholders

withcommon

goals

anda

clearviewof

value

creationAssess

the

currentdata

estate;

outlinetarget

adaptability,

access,

andcontrolsBuild

for

futureneedswithahybrid

cloudfor

scale,access,and

managementRun

thedata

fabricbased

on

how

data

iscaptured,composed,

andconsumedManage

data

through

cloud-centricdata

governance

modelSource:

HFS

Research,

2023?

2023,

HFS

Research3Align

stakeholders

with

common

goalsand

a

clear

view

of

value

creation.As

part

of

their

journey,a

technology

leadertasked

with

leading

the

data

modernizationefforts

for

their

firm

will

need

to

gain

executivebuy-in,

qualify

partnerships,

and

defineoutcomes.

In

addition,

they

will

need

to

buildpartnerships

with

firms

that

know

the

industryand

can

anticipate

the

technologyrequirements.

For

a

global

bank,

changing

thedata

estate

can

create

risk,

but

overwhelmingly,HFS’

polling

of

banking

leaders

indicates

datais

paramount

to

meeting

strategic

priorities(see

Exhibit

2).data

estate.

Capgemini

worked

closely

withalarge

U.S.

bank

to

make

this

happen.

As

thebusiness

leader

from

the

bank

shared

with

HFS,Theamount

oftime

ittook

andthevolumeofdata

washindering

business.

Weneeded

tomodernize

howwemanageddata

todrivemore

holistic

decisionmaking.–Head

ofIntegrated

DataServices,majorNorthFor

large

BFS

firms,

the

challenges

with

data

insilos

limit

profitability,

inhibit

transaction

speed,and

weaken

the

organization’s

ability

to

makethe

sound

decisions

its

customers

expect.

Theneed

to

have

data

as

an

asset

is

critical

todecision-making.

In

the

bank’s

existing

model,making

timely

decisions

was

challenging.

Forexample,

as

isoften

the

case,a

bank

will

haveterabytes

of

data;

as

such,

the

time

needed

toassess

the

accuracy,

inputs,

and

dependenciescannot

effectively

be

cataloged

by

human

effortalone.

Additional

tools

to

automate

discoveryand

assessment

are

crucial

to

modernize

theAmericanbanking

andfinancial

servicesfirmIn

today’s

evolving

financial

markets,

customerneeds

(from

capital

markets

to

retail

banking)and

regulatory

requirements

compound

theneed

for

data

to

improve

asa

working

asset.

Todo

so,

different

parts

of

the

firm

will

needaccess

to

data

pipelines

that

pull

from

a

dataestate

encompassing

all

the

bank’s

data

assets.So

while

shedding

light

on

driven

alignmentcan

be

done,

the

real

work

iswhat

comes

next.Exhibit

2:

Sixtypercent(60%)

of

bankingandfinancial

services

leadersfocus

ondataas

their

firm’s

strategic

priorityRankthetop

threeinitiativesyouarecurrentlyundertakingtohelpmeet

your

organization’sstrategic

priorities.Top

sixshownRank124%Rank220%Rank3Improvingdata

and

anassetand

automatingdata

process16%16%Modernizingapplicationsfor

thecloud9%

4%Improveourabilitytosenseand

respondtomarketshiftsincustomerbehavior13%

7%

11%Makemajorinvestmentsinsecurity

11%2%

2%Learntocompeteagainstdigitaldisruptors

9%

7%Rapidproductor

serviceinnovation

4%4%

9%Sample:

HFS

Pulse,

2022;

n=59

Global

2000

banking

decision-makersSource:

HFS

Research,

2023?

2023,

HFS

Research4With

firms

dealing

with

legacy

models

ofdecentralized

data,

it

is

important

to

assesscurrent

data

estate—the

outline

targetadaptability,

access,

and

controls.?

Develop

asingle

datamaster

plan

where

afederated

lineof

business

applications

orautomation

capabilities

candrawfrom

asinglesource

butcontextualize

datainrelevant

means.Instead,

thedata

problem

weweretryingtosolvewas

the

lackof

aunified

datastrategyacrossall

our

lines

ofbusiness,preventing

thesurfacing

ofdataconsistently

forourbusiness

tomakequalitydecisions.With

the

assessment

completed

andgoalsagreedupon,Capgeminiandthe

bankdecidedtobring

inGoogle’s

cloud

teams

tohelpcraft

thehybrid

cloud

model

thefuturestate

required.

Google

helpsbridgethe

legacyenvironment

with

newtools

atop

asingulardataestate.–Head

ofIntegrated

DataServices,

majorNorthAmericanbanking

andfinancialservicesfirmWhile

federated

dataaddresses

the

needsofindividuallines

of

business,

the

bankrealized

itmustdevelop

aholistic

viewof

anewdatamanagementarchitecture.

Therefore,Capgeminiandthe

Head

of

Integrated

DataServices

implementeda90-dayassessment

ofthe

existing

dataestate.

Theassessmentprovided

significant

technical,process,

security,user,andregulatory

insights,butmostAs

a

partnertoboth

thebank

andGoogle,[Capgemini’s]

roleistosee

ourjointeffortsarenotseen

asjust

atechnology

solution.Rather,they

arepartoftheemergingoperationalculture

inthebank.

Wearen’tsuccessful

ifwearen’t

proactivelylookingfornew

data

uses,

reducing

time

toimportantly,

itoffered

aclearviewof

thechallenges

theteam

would

needto

overcome.Itledto

the

following

core

goals:decision,andimprovingthecoststructuresassociatedwithamodern

data

estate.?

Stop

the

federation

of

duplicate,

disjointeddataacross

multiplelines

of

businessandarchitectures.–AshvinParmar,

VicePresident,Insights

&DataPractice

Leader

atCapgemini?

Implementadatagovernance

framework

tomeetthecompliance

and

investmentrequirements

for

dataaccuracy

andsecuritywithout

weakeningthe

dataasset.?

2023,

HFS

Research5Acentralized

datastrategy

andfederatedmodel

provides

the

adaptability

to

build

forfuture

needs

with

a

hybrid

cloud

for

scale,access,

and

management.Bringing

in

technology

and

services

partners

isessential

to

data

estate

modernization.

Asillustrated

in

Exhibit

3,

the

journey

from

acurrent

model

to

a

target

hybrid-cloud

solutionis

a

multi-step

process

with

many

aspectshappening

in

parallel.

With

many

moving

parts,the

technical

knowledge,

frameworks,

and

toolsto

accelerate

the

discovery

to

deliver

a

run-timeenvironment

will

likely

require

inputs

fromexternal

partners.

Therefore,

it

is

worth

bringingyour

technology

partners

early

and

sharing

theassessment

and

delivery

targets

if

possible.processes,

and

automation

tools

fromassessment

to

management.

In

addition,

thebank

saw

Capgemini

provide

additional

skillsand

methodologies

for

transforming

dataworkloads

with

minimal

business

impact.Capgemini’sprimaryvalue

isthey

hadbusiness

andITcontextrightfromthestart.They

understoodourlegacyenvironment

andhadtheengineeringexpertise

tohelp

us

withourdatachallenges.In

the

case

of

this

North

American

BFS

firm,Capgemini

and

Google

were

selected

aspartners

to

aid

with

their

data

estatemodernization

efforts.

Capgemini

broughtdomain

expertise,

familiarity

with

BFS

business–Head

ofIntegrated

DataServices,majorNorthAmericanbanking

andfinancialservicesfirmExhibit

3:

Transform

yourexisting

data

estateto

onethat

isoptimized

for

hybridclouddelivery.Real-timedata

ingestionanddistillation

ofdata4Converting

andsecuritydata3Application

ofAI/MLtoautomate

theas

adynamic

asset5monitoring,securing,

andgoverning

ofdataDefiningthehybridclouddataestateanddata

pipelines2Contextualizing

data

tobe6usedbyteams

todelivervalueAssessing

anddiscoveringrepositories,

workloads,anddependenciesEnsuringgovernance,17riskandcompliance.The

data

estatemodernizationjourneySource:

HFS

Research,

2023?

2023,

HFS

Research6The

bank

has

multiple

cloud

partners,

but

itchose

Google

because

it

could

deliver

theartificial

intelligence

(AI),

machine

learning

(ML),analytical

requirements,

and

the

high

amountsof

storage

and

computing

needed.

In

addition,having

trusted

partners

brings

many

benefits.For

instance,

Capgemini

brought

a

strongpartnership

with

Google’s

Cloud

Platform

teamto

help

expedite

data

conversion

andincorporate

automation

tools

to

accelerateboth

the

proof

of

concept

and

migrationphases.

This

saved

money

and

time

in

thejourney

and

amplified

the

value

of

thepartnership.The

bank

cited

Capgemini’s

Industrialized

Dataand

AI

Engineering

Acceleration

(IDEA)

asafactor

in

building

its

future

data

needs.Capgemini’s

IDEA

solution

offers

continuousinnovation

of

how

data

is

governed,

accessed,monitored,

optimized,

and

analyzed

in

thecontext

of

changing

business

needs.

Inaddition,

with

its

Big

Query,

cloud-nativedatabase,

storage

offerings,

and

ability

toaugment

or

replace

mainframe

datatechnologies

with

cloud-native

technologies,Google’s

Cloud

provides

alternative

greenfieldand

brownfield

options

for

technology

teams

atthe

bank

orCapgemini

to

implement

andleverage.Regulatory

compliance

also

drives

datamodernization.

The

Basel

Committee

onBanking

Supervision

(BCBS)

239

exemplifieshow

external

regulations

highlight

gaps

banksmust

address

to

comply

with

security,

dataaggregation,

and

reporting.

BCBS

239

acted

asbotha

business

and

technology

accelerator.[AtGoogle,

ourefforts

forourcustomersare]tosupportevery

stageofthedatalifecycle

throughtransactionaldatamanagement,

analytics,warehousing,

datalakes,

andAI/MLsolutions.

Inaddition,

wedoourbesttodevelopsolutionsbasedonopenstandards—soourcustomers

benefitfromfuture-ready

solutions.

Wearealsoproactive

atbringingin

ourecosystem

ofpartnerstomeet

specific

customer

orindustry

needs.–SimonBrown,Partner

Solutions

Architect,SmartAnalyticsatGoogle?

2023,

HFS

Research7IT

andbusiness

must

collaborate

torun

the

recastdata

fabric

based

onhow

datais

captured,composed,

and

consumed,

utilizing

cloud

and

on-premises

data

estates

in

an

interoperable

manner.Modernizing

your

data

estate

must

fit

howtechnology

serves

the

business

needs.

AsExhibit

4

illustrates,

to

be

successful,

our

BFSclient

focused

on

upgrading

its

core

datasystems

usinga

foundation

model

suited

to

theextraction

and

loading

of

data

into

tools

thatcould

present

business

insights,

provide

360-degree

views

of

the

customer’s

assets,

improvetransaction

quality,

and

meet

evolvinggovernance

requirements.?

Compose:

Assembling

data

into

insights

isincreasingly

automated

by

analytic,

artificialintelligence,

and

machine

learning

tools.

Usetools

built

for

augmenting

how

the

data

iscontextualized

for

the

user.?Consume:

The

goal

is

to

increase

the

abilityof

data

and

information

to

drive

timely,

high-quality

decision-making.

Consumingaccurate

data

createsa

value

cycle

ofcapturing

even

more

data

and

improving

thebusiness

in

measurable,

long-term

ways.Byclarifying

how

data

and

insights

fit

intoafirm’s

data

modernization

efforts,

you

can

moreeffectively

develop

a

plan

to

capture,

compose,and

consume

data

across

your

organization:Data

estate

modernization

is

the

foundation

fordelivering

business

insights

through

AI/MLtools.A

firm

can

promote

more

effectiveimplementation,

adoption,

and

innovationbased

on

use

cases

by

adopting

a

hybrid

cloudapproach.

In

addition,

firms

can

increaseproductivity

and

customer

satisfaction

bybuilding

an

architecture

to

deliver

and

promotethe

use

of

data.?

Capture:

Collecting

data

intoa

master

dataestate

will

allow

for

a

universal

approach;

it

issecuring,

governing,

and

distributing

thedata

to

individual

groups

and

systems.However,

without

outlining

the

architectureof

the

data

estate

in

terms

of

data

qualityand

controls,

data

will

quickly

revert

to

afederated

model.Exhibit

4:

Establishing

abalancethatbrings

valuetothetechnology

andbusinessteamsarounddata

and

insightsisessential.Above

thelineimpactNaturallanguage

andpredictive

solutions*Analytics,

AI/MLBusinesssolutionimpactInsightsBusinessintelligenceGovernanceData

lineSecurityAutomation

and

managementMesh*DataTechnologysolutionconcentrationModernizationFoundationBelowthelineimpact*Emerging

technologiesSource:

HFS

Research,

2023?

2023,

HFS

Research8It

is

essential

tomanage

data

through

acloud-centric

data

governance

model.To

succeed

in

data

estate

modernization,converting

froma

federated

data

model

to

onethat

can

be

managed

and

governed

effectivelyis

critical.

The

bank’s

need

for

“ground

tocloud”

and

“cloud

to

ground”

strategiesexemplify

this

need

for

flexibility

in

its

datamodel.

Its

data

management

is

not

aboutcentralizing

the

data

but

rather

architectinghow

it

manages

data

across

multiple

dataprograms,

from

storage

to

warehouses

to

datalake

houses.The

major

BFS

firm

stressesthe

importance

ofrelationship

and

trust

with

its

partner

to

applyits

understanding

of

the

bank’s

people,process,

and

technology

and

be

proactive

withnew

ideas

and

solutions.

For

example,

thepartner

worked

collaboratively

to

identify

thecloud

partners

and

select

how

each

could

bringthe

functionality

needed

for

different

programs.Byseparating

the

needs

of

the

front

officeversus

mission-critical

data

systems,

the

bankcould

apply

its

frameworks

and

domainknowledge

with

the

hyperscaler’s

BFS

and

dataofferings

to

develop

an

optimized

environmentthat

met

operational

and

regulatoryA

data

estate

ecosystem

mindset

puts

data

towork

as

an

asset,

fueling

products,

decisions,and

insights.

Approaching

data

as

an

assetextends

the

availability

of

technology

andbusiness

operations

to

jointly

identifyrequirements.opportunities,

improve

operational

efficiencies,and

increase

the

effectiveness

of

transactionsacross

the

bank

and

its

customers.

Moreover,

asthe

trust

and

usability

of

data

improve,

data

canevolve

intoa

product.

With

data-as-a-product,a

bank

can

grow

its

offerings

or

create

new

cashflow

across

its

lines

of

business

and

its

partners.?

2023,

HFS

Research9The

Bottom

Line:

Break

data

estatemodernization

into

manageablecomponents,

starting

withassessment

and

ending

with

a

clearpath

to

sustainable

value.Modernizingyour

dataestate

requires

equal

effortfrom

technology

andbusinessteams

toachievesuccess.Duetoitscomplexity,

investingwithpartnerswhobring

therightmix

ofexperience,

resources,

industryknowledge,

andtechnical

understanding

iscrucial.Inaddition,

choosingtheright

partnersshouldbolsterco-innovation

capabilities

toensurethebusinessbenefitsfromreal-timeinsights’newfunctionality,flexibility,andfeatures.Finally,asnewparadigms

suchasGenerativeAI

aretransformingthecustomerexperience,

ensuringthequality

andintegrityoftheunderlying

databecomesofparamount

importance.Our

current

and

future

data

effortsmust

not

be

treated

as

a

line

ofbusiness

or

a

single

line

of

business

problem.

[Establishingmy

roleensures]

our

program

is

taken

very

seriously

at

an

enterprise

level.–

Head

of

Integrated

Data

Services,major

North

American

banking

and

financial

services

firm?

2023,

HFS

ResearchMAY

2023

|10HFS

Researc