1.
SNP T-Bon - Dat Provi
ne ta isioning and M
g Masking
timized D
Opt Data for T
Test, Compliance and Qu
e uality Manageme
a ent
Page 1 of 15

2.
Transformations are now a regular pa of every
s art yday busineess. It is not only the b
business
units within a company fa
s c acing increaased levels of pressur due to ra
re apid economic and
technnical changge—their IT organiza
T ations are also feelin the stra
ng ain. Transfoormation
proceesses (mer rgers and a
acquisitions optimizing organizat
s, g tional struct
tures) now happen
much faster, tim
h me-to-marke is increas
et singly shorte
ened for pro
oducts and services an many
nd
comp panies are coming fa ace-to-face with new technologies and op perational cconcepts
(clou services or SaaS models, fo instance)
ud or )—these ar now all part of the daily
re
enterrprise agenda.
Cons sequently, c
companies seeking to d define the m
market going forward c cannot rely o using
on
simp renovatio and optimization me
ple on easures aloone. Modern IT organiz
n zations mus create
st
a sysstem enviroonment that allows for ever-shorte
t ening transfformation cyycles to tak place.
ke
A cru
ucial factor for achievin this is to systematic
ng o cally restruc
cture the co
ompany’s pl latforms,
optim
mize the pr rocesses within the co ompany itse and imp
elf prove the quality of da
q ata—the
objecctive being to significan improve business performanc
ntly e ce.
Commpanies are becoming increasing aware of the imp
e g gly portance of quality as ssurance
within their IT s
system landdscapes. It is a cornersstone of a company’s entire IT o operation
and i a factor that contribu
is utes signific
cantly towar its profita
rd ability and performance results.
e
Commpanies app quality m
ply management and testing measures in order to address im
s o mportant
challenges facin them, s
ng such as err ror-free bus
siness proc cess support, higher levels of
acceeptance and driving a more effic
d cient way o working from the p
of perspective of their
softw
ware users.
Page 2 of 15

3.
If we focus on business software a
e n applications we see that ERP users are running
s,
appli
ication and system lanndscapes th are bec
hat coming incr
reasingly co
omplex and feature
d
an evver-growing number of datasets. In order to ensure tha these sys
g at stems run optimally,
comppanies need to provid their dev
de velopment, test and tr
raining syst
tems with te data
est
that is both apppropriate a
and realistic By doing so, they can then s
c. g speed up ssoftware
deveelopment pr rocesses, aautomate qquality assuurance processes and provide e
d effective
supp when in
port ntroducing n
new busines functions
ss s.
Provvisioning for both initial and recurr
r ring test dat for these purposes must be as flexible
ta e s
as poossible. It m
must be per rformed both quickly an with as l
nd little manua effort as p
al possible,
including prepro ocessing an post-proc
nd cessing activities.
To obtain test data that is rrealistic, companies ca turn to th product
an heir tion environ
nment as
a soource. Seve eral differen procedur
nt res are ava
ailable for building sys
b stems that are not
productive. It is crucial, reg
gardless of what appro oach is used to create a 1:1 copy (clone)
d, e y
using technical tools prov
g vided by ha ardware an database manufact
nd e turers or s
specialist
®
third-
-party proviiders. For eexample, the basic tools available within SAP (such as R3load
e e P s
and RRemote Client Copy) a also allow users to crea a copy o entire sys
ate of stems and c clients.
Howe ever, the di
isadvantage of these a
e approaches is that a co
s onsiderable amount of manual
e f
proce
essing effo ort—particul
larly post-p
processing— require in order to create a test
—is ed e
envir
ronment ou of a production envi
ut ironment (aadjusting au
uthorizations interface users
s, es,
and roles, for e
example). In addition, a significan level of r
n nt redundancy is also generated,
y
which in turn increases the demand for storage capacity ne
e f eeded in or rder to replicate the
wing amount of data av
grow ts vailable within the prod
duction systtem.
Furthhermore, du to reason connecte with stat
ue ns ed tutory data protection r
regulations (BDSG,
TKG, 95/46/EG, HIPAA, et and inte
tc.) ernal guide
elines regard
ding data ssecurity, the is an
ere
significant need to “anon
d nymize” and deperson
d nalize data copied fro the pro
om oduction
envirronment in order to p prevent unauthorized access to sensitive or business-critical
inform
mation suc as busin
ch ness partne address
er ses, salarie conditions and int
es, tellectual
prope (particu
erty ularly acces by extern parties).
ss nal
Page 3 of 15

4.
The Solution
SNP T-Bone Data Provisioning and Masking (DPM)—as a further enhancement to the
d e
“SNP Data Dis
P stillery” that was introduced back in 2006—
t —provides users with a well-
deveeloped, sopphisticated, efficient an agile too for perfo
nd ol orming migrrations and reliably
mask king live da from th
ata heir ERP s systems, fo use in te
or esting, quality assuran
nce and
traini
ing.
As ppart of the o overall SNP T-Bone transformati
P ion platform test data managem
m, a ment and
test d
data anony ymization ha been dev
as veloped fur rther as a separate sol
lution modu SNP
ule:
T-Bo one Data P Provisioning and Mas sking. SNP has developed the m
P module’s un
nderlying
functtionality by drawing on our years o experience gained in this area, paving the way for
of , e
a sollution that m
makes it eas and effic
sy cient to integgrate into te manage
est ement and ttest data
mana agement op perations, from both a logical and technical perspective In the fut
d e. ture, this
will e
enable com mpanies to determine the data needed fro test cases using a semi-
om
autommated or fu automat approac and will allow them to make this data available by
ully ted ch,
mean of a defin scenario.
ns ned
SNP T-Bone Da Provisi
ata ioning and Masking c help co
can ompanies ta
ackle and ov
vercome
the fo
ollowing iss
sues, for exa
ample:
 Building sandbox sy
ystems and project sys
stems
 Refreshing QA syst
tems regula
arly
 Provision
ning test da for developers and colleagues working in support
ata
 Provision
ning selecte test data for process
ed a sing suppor incidents
rt
 Anonymization of da that nee protection in non-p
ata eds production systems
s
By p
providing ussers with a function fo reducing test data in a highly flexible way, users
or
have a tool that allows them to guarantee the qu
e t uality of their software and project at low
ts
cost and with m minimum e effort. Any transformat
tion cycles that are p present in c
complex
em environ
syste nments are shortene conside
e ed erably and both inte ernal projec
cts and
main
ntenance ac ctivities are supported extremely fl
e lexibly.
Page 4 of 15

5.
Figur 1 - SNP T-Bone Da Provisio
re T ata oning and M
Masking - Architecture
A e
A ho of selec
ost ction option allow us
ns sers to resp
pond to pro
oject requir
rements wi great
ith
flexib
bility. It als enables them to supply the various different test phases within
so s t s
Application Life ecycle Mana agement, s
such as bug fixing, un tests, int
g nit tegration te
ests and
proce tests, with suitable test data.
ess w e
The DPM modu differenti
ule iates between the following use ca
ases:
Use
U Case Processs
Unit tests / dev
t veloper tests
s - Provisioning up-to-date master dat for
P g e ta
developmen systems
d nt
- Object-depe
O endent selecction of bus
siness
processes
p
Inte
egration test / interface tests
ts e - Time-based data reduc
T ction
- Complete client transfer
C
Page 5 of 15

6.
Use
U Case Processs
Sup
pport incidents / bug fix
xing - Object-depe
O endent selec
ction
Training system
m - In
ndividual co
ombination of various r
o reduction
processes in order to co
p n over all rele
evant
tr
raining meaasures while maximizin data
e ng
re
eduction
Com
mpliance requirements
s - “P
Post ante” anonymiza ation of the test data
e a
tr
ransferred d
during migra
ation
- “P
Post ex” anonymization of existing g
data/system
d ms
The DPM modu supports periodic da refreshe this enables compa
ule s ata es; anies to sign
nificantly
reduc the effo required (along with the need for post-processing activities, allowing
ce ort d)
them to compen
m nsate for any adverse time-relate effects t
e ed that may arrise. The voolume of
data made ava ailable for testing in test system is able to be reduced consi
t ms iderably.
Neveertheless, the test data still sus
stains a gre level of consisten
eat f ncy in spite of this
e
reduc
ction thank to taking the depen
ks g ndencies th exist w
hat within busine processes into
ess
cons
sideration.
By applying a s series of anonymization rules flexibly, individual complia
n ance guidelines are
met and, in part uirements regarding th issues th surround offshore a
ticular, requ he hat d activities
are ffulfilled. The set of rul used by the DPM module is based on the tables that are
e les y
defin in the data scenarios. It takes into account the most crucial req
ned t quirements, such as
the fo
ollowing:
 Ensuring referential integrities
g l
 Repeate anonymiz
ed zation and irreversible anonymiza
i ation
 Retaining the chara
acteristics of production data
f n
 Ability to activate or deactivate anonymiza
o r e ation for eac scenario
ch o
SNP T-Bone D Data Provissioning an Masking enables you to supply your ERP test,
nd g y
deveelopment an training systems with consiste data accurately ch
nd ent hosen and o obtained
from within you productio system. Standard m
ur on methods th are ava
hat ailable for p
providing
data from no on-productio
on ERP systems b bring with them se everal rec cognized
dvantages:
disad
 A system copy can only crea clones; you there
m ate efore have to reserve a huge
amount of storage c
capacity for data that y do not a
r you actually nee Furtherm
ed. more, an
Page 6 of 15

7.
extensive amount o manual post-processing is nee
of p eded in the target syste (e.g.
em
for interf
faces, users printer configuration and so on Anonym
s, n n). mization—a process
which yo may requ
ou uire—is not included as part of a system copy
s s y.
 Similarly client cop
y, pies also do not offer as much selection po
o ower, and th also
hey
demand a lot of sto orage space for unnece
e essary data volumes. Furthermor when
a re,
the volum of data involved is over 200 GB, the tim required to perform a client
me s me m
copy is simply far too long. Again, the process of anonymiza
A f ation that y
you may
require is not includ as part of a client c
s ded copy either.
SNP T-Bone Da Provisi
ata ioning and Masking a
allows you t restrict data to the b
to business
proceesses and objects tha you actua require, along with their underlying tables. This
at ally h
offers several ke IT production and m
s ey managemen advantage
nt es:
 Both the time needed to fill your non-p
e production systems an the amo
nd ounts of
storage space required for them are reduc conside
s m ced erably.
 Your dev
velopment and training systems become m
more efficien and are s
nt supplied
with new production data at sh
w n horter intervals and with shorter do
h owntimes.
Figur 2 - SNP T-Bone Da Provisio
re T ata oning and M
Masking - Efficiency
E
Page 7 of 15

8.
The sophisticatted anonym mization fu
unctions included as part of SSNP T-Bon Data
ne
Provvisioning and Maskin guarante that any sensitive data you ma have will always
a ng ee d ay
be kkept out of the reach of any un nauthorized parties. U
Using anony
ymized pro
oduction-
relate test data in this way
ed a y:
 Guarante
ees all bus
siness proc
cesses can be tested while taki
n d ing data pr
rotection
regulatio into acc
ons count
 Enables you to cond
duct perform
mance tests using real
s listic data vo
olumes
 Allows you to use liv processe in a reali
ve es istic test environment d
during testin
ng
 Avoids th time-con
he nsuming pro
ocess of hav
ving to crea synthetic test data.
ate c
Page 8 of 15

9.
Func
ctionalities
s
SNP T-Bone Da Provisioning and Masking p
ata provides use with a highly intellig
ers gent and
efficient data exxtraction too that goes far beyon standard ERP tools Using pre
ol s nd d s. edefined
extraaction rules (such as seelection par
rameters or table depe
r endencies) as its basis, SNP T-
a ,
Bone Data Prov
e visioning a and Maskin helps to simplify the process of selecting t
ng e f test data
significantly.
ses busines
It us ss-object-re
elated scennarios to en
ncapsulate a complex set of ru
x ules that
desccribe dependencies tha exist betw
at ween business entities and datab
s base tables in great
detai all you h
il: have to do is simply select whi
o ich process
ses, transa
actions or b
business
entiti are to be tested. Mechanisms included within the SN T-Bone Data Provi
ies e NP isioning
and Masking so olution then perform th following system-based processing steps.
n he
Figur 3 - The S
re SNP T-Bone Data Provisioning a
e and Maskin - Data M
ng Model
Page 9 of 15

10.
Poss
sible Scena
arios
SNP T-Bone D Data Provissioning and Masking is a univer
d rsal solution that provi
n ides you
with support for conducting training eff
g ficiently or f building extensive test scenario
for os.
mples of possible scenarios includ
Exam de:
 rring master data and t
Transfer r transaction data of a client without reduction
t
 Reducing transactio data acc
on cording to tim
me-based restrictions
 Transfer
rring master data witho any trans
r out saction data
a
 Selecting master d
g data and tr wing areas using a
ransaction data from the follow
business
s-object-rela
ated approa
ach:
 ERP System
E m
 IS / IS-T
S-U
 FS-CD
F
 FI-CA
F
 CML
C
 CFM
C
 Retail
R
 Performi “post ex anonymiz
ing x” zation of exi
isting clients
 Performi individual migration of data / table conte for test s
ing ns ent systems (red
duced
or in full)
)
Page 10 of 15
P

11.
Data Extraction Modes
a n
In or
rder to suppport the different scenarios and issues tha exist when setting up non-
at
production systems, SNP T-Bone Da Provisioning and Masking offers a va
ata d ariety of
data extraction m
modes, deppending on the scenario chosen:
 “Intellige Data Ext
ent traction” mo
ode:
 A sub ects are extracted along with their related dat environm
bset of obje ta ment
 Objects being extracted
d are se
elected at
t business
s level explicitly
e
(proc
cess/transac
ction/entity)
)
 Only selected objects along with their dependent objects are extracted
g e
 “X% / Ma Extraction” mode:
ass
 All ob able within the system are extract
bjects availa ted
 Certa objects are exclude (e.g. use data, IDoc
ain ed er cs)
 Amount of data can be reduced by a
a applying various differe selectio (e.g.
ent ons
comp
pany code 1
1000)
Anon
nymization Function
n
Anonnymization is performe at field le
ed evel during the data tra
ansfer. Any measures needed
y
are d
defined usin simple ru
ng ules as par of custom
rt mizing. Commplex rules a implemented in
are
the fo of a fun
orm nction modu
ule.
Exam
mples of anonymization rules inclu
n ude:
 Address and contac data relat
ct ting to custo
omers, vendors and bu
usiness par
rtners as
part of ensuring refe
erential inte
egrity
 Using a constant v
value to ov ank details to avoid back-referencing to
verwrite ba b
custome or compa
ers anies
 Using fix values t overwrite cost cente managers and cost center texts
xed to e er s c
Page 11 of 15
P

12.
Fea
atures
The features lis
sted below are what set SNP T-
s -Bone Data Provision
a ning and M
Masking
apart from other solutions:
t r
Data Provision
a ning
 No restri
iction to cer
rtain ERP m
modules only
y
 Customizing, maste data and transaction data are all taken into considerat
er n o tion
 Custome developm
er ments are su
upported
 Support provided f Industry ERP Solu
for y utions (IS-U IS-T, FS
U, S-CD, Reta CML,
ail,
CFM) as part of the standard c
s e content
 Developing separat customer scenarios on top of th standard content
te r he
 mensional data distinction
Multi-dim
 User-frie
endly user in
nterface
 Saving “data containers” in flat files to restore fixed system statu
t uses
 Converti names o logical sy
ing of ystems on-the-fly
 Setting u and trans
up sferring multiple clients in parallel
s
 Compen
nsating for s
structure diff
ferences
 Migrating across dif
g fferent relea
ases
Page 12 of 15
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13.
Data Masking
a
 rformance d
High-per data transfe / anonymization as standard sof
er s ftware
 Centraliz customizing enable settings to be reuse
zed es ed
 calable due to parallel data proces
Highly sc e ssing and o
optimizing h
hardware uti
ilization
 Masking fields that need protec
cting at data record lev
a vel
 Consiste anonym
ent mization, me
eaning name and add
es dresses are anonymize in the
ed
same wa during ea refresh
ay ach
 Compreh
hensive sup
pport for numerous lea
ading ERP c
components
s
 Uniform anonymiza
ation of redu
undant data within the s
system
 ized anonym
Harmoni mization log used for all systems within the landscape
gic r s
The data involv remains protected at all times as the data extracto used as part of
ved s s, ors s
SNP T-Bone D Data Provissioning and Masking only have read acce to the d
g e ess datasets
within your prodduction sys
stems. Optio
onal deletio runs can be used t ensure that your
on n to
data is kept con
nsistent.
mmary
Sum
SNP T-Bone D Data Provissioning and Masking— a furth enhanc
d —as her cement to th “SNP
he
Data Distillery”—
a —provides users with a well-developed, sopphisticated, efficient and agile
tool f performing migratio and reliably masking their live ERP data for use in testing,
for ons a n
quali assuranc and train
ity ce ning. By foc
cusing clear on the ap
rly pplication area in quesstion and
proviiding intuitive user gu
uidance, us sers can aachieve the highest levels of e
e efficiency
posssible.
 Scenario can be extended flexibly with th user-frien
os he ndly custom
mizing interf
face
 Complies with statu
utory data protection an data eco
nd onomy regul
lations
 Maskking rules a applied before any data leave the produ
are es uction envir
ronment;
ad-ho masking is used for existing test environm
oc g r ments
 Data objects being transfer
rred can by restricted extremely fle
e exibly
Page 13 of 15
P

14.
 Data ma
asking is use for each mode of op
ed peration
 Reduced and mask data ext
d ked tracts are backed up, m
managed an re-used
nd
 Administ
trative preprocessing and post-pro
a ocessing tasks are red
duced
 Clien and logica systems are convert automat
nt al ted tically
 User master, au
r uthorizations customizing and the repository are all retained
s, e
 Any o
other clients and cross
s s-client data are not changed in an way
a ny
 Predefin scenari for ERP environme
ned ios ents (from Release 12.4
R 4)
 Clien transfer fe
nt eaturing opt
tional, flexib reductio options
ble on
 Time
e-based data reduction
 Busin
ness object selection
t
 Effici
ient deletion of non-pro
n oductive clie
ents
 Direct da transfer using RFC or file inter
ata C rface
Integ
grated direc within th SNP T-Bone transfo
ctly he ormation pla
atform, SNP T-Bone Da
P ata
Provvisioning and Masking l
d lets you furt
ther optimiz complex testing and quality ass
ze d surance
mech hanisms. Upstream proocesses inv volving scan and analyses are su
ns upported, as well
s
as fu integratio into your central proj
ull on ject management.
peration can benefit from using the DPM mod
Plus, your IT op
, n e dule in comb
bination with other
h
SNP T-Bone mo odules, enaabling you to realize mo complex methods, such as go
o ore x oal-
base procedur and dynamic test procedures.
ed res
.
Page 14 of 15
P

15.
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yright 2012 SNP AG. A rights res
All served
No pa of this pub
art blication may be reproduc
ced or transmitted in any f
form or for an purpose w
ny without the
express permission of SNP AG. T informatio contained h
n The on herein may be changed with
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SNP. This documen contains on intended st
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Page 15 of 15