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Snp T bone-dpm_overview


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Snp T bone-dpm_overview

  1. 1.  SNP T-Bon - Dat Provi ne ta isioning and M g Masking timized DOpt Data for T Test, Compliance and Qu e uality Manageme a ent Page 1 of 15   
  2. 2.  Transformations are now a regular pa of every s art yday busineess. It is not only the b businessunits within a company fa s c acing increaased levels of pressur due to ra re apid economic andtechnnical changge—their IT organiza T ations are also feelin the stra ng ain. Transfoormationproceesses (mer rgers and a acquisitions optimizing organizat s, g tional struct tures) now happenmuch faster, tim h me-to-marke is increas et singly shorte ened for pro oducts and services an many ndcomp 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 reenterrprise agenda.Cons sequently, c companies seeking to d define the m market going forward c cannot rely o using onsimp renovatio and optimization me ple on easures aloone. Modern IT organiz n zations mus create sta sysstem enviroonment that allows for ever-shorte t ening transfformation cyycles to tak place. keA 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—theobjecctive being to significan improve business performanc ntly e ce.Commpanies are becoming increasing aware of the imp e g gly portance of quality as ssurancewithin their IT s system landdscapes. It is a cornersstone of a company’s entire IT o operationand i a factor that contribu is utes signific cantly towar its profita rd ability and performance results. eCommpanies app quality m ply management and testing measures in order to address im s o mportantchallenges facin them, s ng such as err ror-free bus siness proc cess support, higher levels ofacceeptance and driving a more effic d cient way o working from the p of perspective of theirsoftw ware users. Page 2 of 15   
  3. 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 dan 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 estthat is both apppropriate a and realistic By doing so, they can then s c. g speed up ssoftwaredeveelopment pr rocesses, aautomate qquality assuurance processes and provide e d effectivesupp 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 sas 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 asa soource. Seve eral differen procedur nt res are ava ailable for building sys b stems that are notproductive. It is crucial, reg gardless of what appro oach is used to create a 1:1 copy (clone) d, e yusing 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 sand 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 fproce essing effo ort—particul larly post-p processing— require in order to create a test —is ed eenvir 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, ywhich in turn increases the demand for storage capacity ne e f eeded in or rder to replicate the wing amount of data avgrow 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 eresignificant need to “anon d nymize” and deperson d nalize data copied fro the pro om oductionenvirronment in order to p prevent unauthorized access to sensitive or business-criticalinform mation suc as busin ch ness partne address er ses, salarie conditions and int es, tellectualprope (particu erty ularly acces by extern parties). ss nal Page 3 of 15   
  4. 4.  The SolutionSNP 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 reliablymask king live da from th ata heir ERP s systems, fo use in te or esting, quality assuran nce andtraini ing.As ppart of the o overall SNP T-Bone transformati P ion platform test data managem m, a ment andtest 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 nderlyingfuncttionality by drawing on our years o experience gained in this area, paving the way for of , ea sollution that m makes it eas and effic sy cient to integgrate into te manage est ement and ttest datamana agement op perations, from both a logical and technical perspective In the fut d e. ture, thiswill e enable com mpanies to determine the data needed fro test cases using a semi- omautommated or fu automat approac and will allow them to make this data available by ully ted ch,mean of a defin scenario. ns nedSNP T-Bone Da Provisi ata ioning and Masking c help co can ompanies ta ackle and ov vercomethe 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 sBy p providing ussers with a function fo reducing test data in a highly flexible way, users orhave a tool that allows them to guarantee the qu e t uality of their software and project at low tscost and with m minimum e effort. Any transformat tion cycles that are p present in c complex em environsyste nments are shortene conside e ed erably and both inte ernal projec cts andmain ntenance ac ctivities are supported extremely fl e lexibly. Page 4 of 15   
  5. 5.  Figur 1 - SNP T-Bone Da Provisio re T ata oning and M Masking - Architecture A eA ho of selec ost ction option allow us ns sers to resp pond to pro oject requir rements wi great ithflexib bility. It als enables them to supply the various different test phases within so s t sApplication Life ecycle Mana agement, s such as bug fixing, un tests, int g nit tegration te ests andproce tests, with suitable test data. ess w eThe 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. 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 msThe DPM modu supports periodic da refreshe this enables compa ule s ata es; anies to sign nificantlyreduc 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 ofdata 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 ereduc ction thank to taking the depen ks g ndencies th exist w hat within busine processes into esscons sideration.By applying a s series of anonymization rules flexibly, individual complia n ance guidelines aremet and, in part uirements regarding th issues th surround offshore a ticular, requ he hat d activitiesare ffulfilled. The set of rul used by the DPM module is based on the tables that are e les ydefin in the data scenarios. It takes into account the most crucial req ned t quirements, such asthe 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 oSNP T-Bone D Data Provissioning an Masking enables you to supply your ERP test, nd g ydeveelopment an training systems with consiste data accurately ch nd ent hosen and o obtainedfrom within you productio system. Standard m ur on methods th are ava hat ailable for p providingdata 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. 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 businessproceesses and objects tha you actua require, along with their underlying tables. This at ally hoffers 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. 8.  The sophisticatted anonym mization fu unctions included as part of SSNP T-Bon Data neProvvisioning and Maskin guarante that any sensitive data you ma have will always a ng ee d aybe 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. 9.  Func ctionalities sSNP T-Bone Da Provisioning and Masking p ata provides use with a highly intellig ers gent andefficient data exxtraction too that goes far beyon standard ERP tools Using pre ol s nd d s. edefinedextraaction 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 datasignificantly. ses businesIt us ss-object-re elated scennarios to en ncapsulate a complex set of ru x ules thatdesccribe dependencies tha exist betw at ween business entities and datab s base tables in greatdetai all you h il: have to do is simply select whi o ich process ses, transa actions or b businessentiti are to be tested. Mechanisms included within the SN T-Bone Data Provi ies e NP isioningand Masking so olution then perform th following system-based processing steps. n heFigur 3 - The S re SNP T-Bone Data Provisioning a e and Maskin - Data M ng Model Page 9 of 15   
  10. 10.  Poss sible Scena ariosSNP T-Bone D Data Provissioning and Masking is a univer d rsal solution that provi n ides youwith support for conducting training eff g ficiently or f building extensive test scenario for os. mples of possible scenarios includExam 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. 11.  Data Extraction Modes a nIn or rder to suppport the different scenarios and issues tha exist when setting up non- atproduction systems, SNP T-Bone Da Provisioning and Masking offers a va ata d ariety ofdata 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 nAnonnymization is performe at field le ed evel during the data tra ansfer. Any measures needed yare d defined usin simple ru ng ules as par of custom rt mizing. Commplex rules a implemented in arethe 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. 12.  Fea aturesThe features lis sted below are what set SNP T- s -Bone Data Provision a ning and M Maskingapart from other solutions: t rData 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  P  
  13. 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 sThe data involv remains protected at all times as the data extracto used as part of ved s s, ors sSNP T-Bone D Data Provissioning and Masking only have read acce to the d g e ess datasetswithin your prodduction sys stems. Optio onal deletio runs can be used t ensure that your on n todata is kept con nsistent. mmarySumSNP T-Bone D Data Provissioning and Masking— a furth enhanc d —as her cement to th “SNP heData Distillery”— a —provides users with a well-developed, sopphisticated, efficient and agiletool f performing migratio and reliably masking their live ERP data for use in testing, for ons a nquali assuranc and train ity ce ning. By foc cusing clear on the ap rly pplication area in quesstion andproviiding intuitive user gu uidance, us sers can aachieve the highest levels of e e efficiencyposssible.  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. 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 rfaceInteg grated direc within th SNP T-Bone transfo ctly he ormation pla atform, SNP T-Bone Da P ataProvvisioning and Masking l d lets you furt ther optimiz complex testing and quality ass ze d surancemech hanisms. Upstream proocesses inv volving scan and analyses are su ns upported, as well sas fu integratio into your central proj ull on ject management. peration can benefit from using the DPM modPlus, your IT op , n e dule in comb bination with other hSNP 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. 15.  Copy yright 2012 SNP AG. A rights res All servedNo pa of this pub art blication may be reproduc ced or transmitted in any f form or for an purpose w ny without theexpress permission of SNP AG. T informatio contained h n The on herein may be changed with e hout prior notic ce.Some software products markete by SAP AG and its distributors contain proprietary s e ed G n software comp ponents ofother software vend dors. soft, Windows Outlook, and PowerPoint are registered trademarks of Microsoft Corporation.Micros s, d d o CIBM, DDB2, DB2 Uni iversal Databa ase, OS/2, Pa arallel Sysplex, MVS/ESA, AIX, S/390, AS A S/400, OS/390 OS/400, 0,iSerie pSeries, xS es, Series, zSeries z/OS, AFP, Intelligent Mi s, , iner, WebSphere, Netfinity, Tivoli, and Informix aretrademmarks or regis stered trademaarks of IBM Co orporation in t United Sta the ates and/or oth countries. herOracle is a registere trademark of Oracle Cor e ed rporation.UNIX, X/Open, OSF and Motif are registered trademarks of the Open Group. , F/1, f d GCitrix, ICA, Program Neighborho ood, MetaFra ame, WinFram VideoFram and MultiWin are trade me, me, emarks orregisteered trademar of Citrix Sy rks ystems, Inc.HTML XML, XHT L, TML and W3C are tradem C marks or registered tradem marks of W3C®, World W Wide WebConso ortium, Massa achusetts Institute of Techno ology.Java i a registered trademark of Sun Microsys is d f stems, Inc.JavaSScript is a reg gistered tradem mark of Sun M Microsystems, Inc., used under license f technology invented for yand im mplemented by Netscape.MaxD is a trademark of MySQL AB, Sweden. DB LThe innformation in t this document is proprietary to SNP. No part of this do t y ocument may be reproduce copied, ed,or tran nsmitted in an form or for a purpose without the exp ny any w press prior wriitten permissio of SNP AG on G.This d document is a preliminary ve ersion and no subject to yo license agreement or an other agree ot our ny ement with ®SNP. This documen contains on intended st nt nly trategies, deve elopments, an functionaliti of the SNP product nd ies Pand is not intended to be bindin upon SNP to any partic s d ng cular course of business, product strateg and/or o p gy,develo opment. Pleas note that th document is subject to change and m be chang by SNP at any time se his may gedwithou notice. utSNP a assumes no responsibility f errors or o r for omissions in th document. SNP does no warrant the accuracy his ot eor commpleteness of the informattion, text, graphics, links, o other items contained within this mat or s w terial. Thisdocumment is provided without a w warranty of an kind, either express or im ny mplied, includin but not limited to the ngimplie warranties o merchantab ed of bility, fitness fo a particular purpose, or n or non-infringemeent.SNP shall have no liability for d o damages of a any kind inclu uding without limitation dire ect, special, in ndirect, orconse equential dama ages that may result from th use of thes materials. T y he se This limitation shall not apply in casesof inte or gross ne ent egligence. © Cop pyright SNP AG, 2012. All rights reserved. , sAll other products mentioned in this d document are re egistered or unregistered tradem marks of their re espective comp panies.  P Page 15 of 15