[{"data":1,"prerenderedAt":369},["ShallowReactive",2],{"blog-\u002Fblog\u002Fdata-migration-for-finance-systems":3,"blog-surround-\u002Fblog\u002Fdata-migration-for-finance-systems":348,"blog-related-\u002Fblog\u002Fdata-migration-for-finance-systems":356},{"id":4,"title":5,"audience":6,"body":10,"cluster":313,"date":314,"description":315,"draft":316,"extension":317,"factCheckedAt":318,"faq":319,"featured":316,"language":318,"meta":329,"navigation":330,"order":331,"originalAsset":318,"path":332,"pillar":333,"primaryKeyword":334,"relatedProject":318,"releaseScope":318,"reviewCycle":335,"reviewStatus":336,"reviewedBy":337,"searchIntent":338,"seo":339,"sources":318,"stem":340,"tags":341,"type":346,"updated":314,"__hash__":347},"blog\u002Fblog\u002Fdata-migration-for-finance-systems.md","Data Migration for Finance Systems",[7,8,9],"engineering-manager","solution-architect","finance-transformation-lead",{"type":11,"value":12,"toc":299},"minimark",[13,36,41,59,63,70,76,79,83,110,114,147,150,154,165,169,176,180,196,200,211,215,230,234,266,273,276],[14,15,16,26,27,31,32,35],"p",{},[17,18,19,20,25],"strong",{},"Data migration is the process of moving data from the old finance system to the new one — extracting, cleansing, mapping, loading and reconciling it — and it's the highest-risk part of a ",[21,22,24],"a",{"href":23},"\u002Fblog\u002Fcutover-and-go-live-for-finance-systems","cutover","."," Two things make it dangerous: finance data must be complete and correct ",[28,29,30],"em",{},"to the penny"," (a wrong balance or a lost open item corrupts the books from day one), and source data is ",[28,33,34],{},"always"," dirtier than anyone expects. Migration is far less a technical load than a data-quality project wearing a technical costume — and teams that treat it as the former are the ones whose migrations run late and land wrong.",[37,38,40],"h2",{"id":39},"what-it-is","What it is",[14,42,43,44,47,48,51,52,55,56,25],{},"Migration takes the data your business depends on and moves it into a new home with a different structure. It's not a copy-paste; it's extract, clean, reshape to the new model, load, and — the step everyone shortchanges — ",[28,45,46],{},"prove it's right",". In finance, the payload is three layers: ",[17,49,50],{},"master data",", ",[17,53,54],{},"opening balances",", and ",[17,57,58],{},"open items",[37,60,62],{"id":61},"why-its-the-riskiest-part","Why it's the riskiest part",[14,64,65,66,69],{},"Most systems start empty and fill up. Finance systems start ",[28,67,68],{},"full",", with the whole past carried forward — so migration isn't a nice-to-have, it's the foundation the new system stands on. And the source is never clean:",[71,72,73],"pull-quote",{},[14,74,75],{},"Every finance data migration reveals the same secret: the old system was full of data that never quite reconciled either. Migration is where a decade of small data sins finally have to be paid off.",[14,77,78],{},"Duplicates, gaps, inconsistent codes, balances that never tied — it's all there, and now it has to be confronted rather than tolerated.",[37,80,82],{"id":81},"the-layers","The layers",[84,85,86,98,104],"ul",{},[87,88,89,92,93,97],"li",{},[17,90,91],{},"Master data first."," Accounts, entities, ",[21,94,96],{"href":95},"\u002Fblog\u002Fsegregation-of-duties-in-treasury-systems","bank details",", counterparties, standing instructions. Everything else references it, so it's migrated and validated before anything transactional.",[87,99,100,103],{},[17,101,102],{},"Opening balances."," The carried-forward position at the cut — which must tie exactly to the old system.",[87,105,106,109],{},[17,107,108],{},"Open items."," In-flight invoices, unreconciled payments, open deals — the transactions that must continue their life in the new system, none lost.",[37,111,113],{"id":112},"the-process-extract-cleanse-map-load-reconcile","The process: extract, cleanse, map, load, reconcile",[115,116,117,123,129,135,141],"ol",{},[87,118,119,122],{},[17,120,121],{},"Extract"," the data from the legacy system.",[87,124,125,128],{},[17,126,127],{},"Cleanse"," it — fix duplicates, gaps and inconsistencies. Usually the biggest, most-underestimated effort.",[87,130,131,134],{},[17,132,133],{},"Map and transform"," it from the old data model to the new one, where the same concept is often structured differently.",[87,136,137,140],{},[17,138,139],{},"Load"," it into the new system.",[87,142,143,146],{},[17,144,145],{},"Reconcile and validate"," — prove the loaded data equals the source.",[14,148,149],{},"The last step is not optional and not a formality; it's the point.",[37,151,153],{"id":152},"data-quality-is-a-workstream-not-a-task","Data quality is a workstream, not a task",[14,155,156,157,160,161,164],{},"The single biggest planning error is treating cleansing as a step rather than a ",[28,158,159],{},"workstream",". Dirty source data is the norm, and cleaning it takes time, business knowledge and decisions (\"these 400 records are duplicates — which survives?\"). Start it ",[28,162,163],{},"early",", run it in parallel, and staff it with people who understand the data — not as a scramble the week of cutover.",[37,166,168],{"id":167},"mapping-old-model-to-new","Mapping old model to new",[14,170,171,172,175],{},"The old and new systems rarely model the same concept identically — a field in one is three in the other; a code scheme changes. Mapping is where those decisions get made and documented. Get it wrong and data lands in the wrong place ",[28,173,174],{},"looking"," fine, which is worse than an obvious failure.",[37,177,179],{"id":178},"reconciliation-prove-it-dont-hope-it","Reconciliation: prove it, don't hope it",[14,181,182,183,186,187,191,192,195],{},"Every migrated layer is reconciled with ",[17,184,185],{},"control totals"," — record counts and amount sums, source versus target — exactly as with any ",[21,188,190],{"href":189},"\u002Fblog\u002Finterface-monitoring-and-reconciliation","interface",". Source has 12,438 open items totalling €X; target must have 12,438 totalling €X. Counts catch losses; sums catch corruption. And it ends in an explicit ",[17,193,194],{},"sign-off"," that the migrated data is accepted.",[37,197,199],{"id":198},"rehearse-it-mock-migrations","Rehearse it: mock migrations",[14,201,202,203,206,207,210],{},"Like cutover itself, migration should not be run live for the first time. Do ",[17,204,205],{},"mock migrations"," — trial loads on real data — to find the problems (bad mappings, missed cleansing, load errors) while they're cheap. Each rehearsal improves the runbook; the live migration should be the ",[28,208,209],{},"n","th time you've done it.",[37,212,214],{"id":213},"how-much-history","How much history?",[14,216,217,218,221,222,225,226,229],{},"A common trap is migrating ",[28,219,220],{},"everything",". Usually you migrate master data, open items and opening balances — the data the new system needs to ",[28,223,224],{},"operate"," — and ",[17,227,228],{},"archive"," the closed historical detail rather than dragging years of it across. Migrating too much history adds risk and effort for data you could keep accessible elsewhere. Decide the cut deliberately.",[37,231,233],{"id":232},"what-usually-goes-wrong","What usually goes wrong",[84,235,236,242,248,254,260],{},[87,237,238,241],{},[17,239,240],{},"Underestimating cleansing."," Treating dirty data as an edge case instead of the main event, so the timeline blows.",[87,243,244,247],{},[17,245,246],{},"Migrating garbage."," Loading dirty data faithfully — now it's dirty in the new system too.",[87,249,250,253],{},[17,251,252],{},"No reconciliation."," \"It loaded\" mistaken for \"it's correct,\" so a wrong balance surfaces in the first close.",[87,255,256,259],{},[17,257,258],{},"No rehearsal."," A big-bang live migration with no mock run, so every surprise lands at the worst moment.",[87,261,262,265],{},[17,263,264],{},"Migrating too much history."," Hauling years of closed data across, adding risk for little value.",[14,267,268,269,272],{},"Cleanse early as a real workstream, map deliberately, reconcile every layer to the penny, rehearse with mock loads, and migrate only the history you need — and data migration stops being the thing that quietly corrupts the new system and becomes the solid foundation a clean ",[21,270,271],{"href":23},"go-live"," stands on. Get the data right, and most of cutover's risk is already behind you.",[274,275],"hr",{},[14,277,278],{},[28,279,280,281,285,286,289,290,293,294,298],{},"Part of the ",[21,282,284],{"href":283},"\u002Ftopics\u002Ffinance-systems-delivery","Finance Systems Delivery guide",". See also ",[21,287,288],{"href":23},"cutover and go-live"," and ",[21,291,292],{"href":189},"interface monitoring and reconciliation",". The ",[21,295,297],{"href":296},"\u002Fnewsletter","newsletter"," sends one finance-systems pattern, product decision or build lesson every two weeks.",{"title":300,"searchDepth":301,"depth":301,"links":302},"",2,[303,304,305,306,307,308,309,310,311,312],{"id":39,"depth":301,"text":40},{"id":61,"depth":301,"text":62},{"id":81,"depth":301,"text":82},{"id":112,"depth":301,"text":113},{"id":152,"depth":301,"text":153},{"id":167,"depth":301,"text":168},{"id":178,"depth":301,"text":179},{"id":198,"depth":301,"text":199},{"id":213,"depth":301,"text":214},{"id":232,"depth":301,"text":233},"execution","2026-07-23","Finance data migration — extract, cleanse, map, load and reconcile into a new system — is the riskiest part of a cutover. Source data is always dirty.",false,"md",null,[320,323,326],{"question":321,"answer":322},"What is data migration in a finance system implementation?","Data migration is the process of moving data from the old system to the new one — extracting it, cleansing it, mapping and transforming it to the new system's model, loading it, and reconciling the result to prove it arrived complete and correct. In finance, it covers master data, opening balances and open items. It's usually the single highest-risk part of a cutover, because the migrated data has to be complete and correct to the penny and the source data is almost always dirtier than expected.",{"question":324,"answer":325},"Why is data migration the riskiest part of a finance implementation?","Because finance carries the past forward and the numbers must reconcile exactly. A wrong opening balance or a lost open item corrupts the books from day one and can take months to unwind. On top of that, source data is reliably dirty — duplicates, gaps, inconsistent codes, values that never reconciled in the old system either — so migration is as much a data-cleansing project as a technical load. Underestimating that cleansing effort is the classic way migrations run late and land wrong.",{"question":327,"answer":328},"How do you make sure migrated data is correct?","Reconcile every layer using control totals — compare record counts and amount sums in the source against what loaded into the target, for master data, balances and open items, and don't consider migration done until they match. Run mock migrations (trial loads) on real data before the live one to find problems early, cleanse the source data ahead of time, and get an explicit sign-off that the migrated data is accepted. Migration isn't finished when data loads; it's finished when the loaded data is proven equal to the source.",{},true,7.3,"\u002Fblog\u002Fdata-migration-for-finance-systems","finance-systems-delivery","finance data migration","annual","reviewed","Tan Gravam","informational",{"title":5,"description":315},"blog\u002Fdata-migration-for-finance-systems",[342,343,24,344,345],"delivery","data-migration","finance-systems","implementation","text","yjY_m778peoLGRSpj15zJnRwshSCmujAD614xn2YSoE",[349,352],{"title":350,"path":23,"stem":351,"type":346,"language":318,"draft":316,"children":-1},"Cutover and Go-Live for Finance Systems","blog\u002Fcutover-and-go-live-for-finance-systems",{"title":353,"path":354,"stem":355,"type":346,"language":318,"draft":316,"children":-1},"Debt and Investment Management in Treasury","\u002Fblog\u002Fdebt-and-investment-management-in-treasury","blog\u002Fdebt-and-investment-management-in-treasury",[357,361,365],{"path":358,"title":359,"description":360},"\u002Fblog\u002Ffit-gap-analysis-for-finance-systems","Fit-Gap Analysis for Finance Systems","A fit-gap analysis compares what a standard system does against what the business needs — fit, gap, or change the process. Avoiding the customization trap.",{"path":362,"title":363,"description":364},"\u002Fblog\u002Fsolution-design-and-blueprint-for-finance-systems","Solution Design and Blueprint for Finance Systems","How to turn agreed requirements into a signed solution design before build starts — and why skipping the blueprint is what quietly buys you months of rework.",{"path":366,"title":367,"description":368},"\u002Fblog\u002Fconfiguration-vs-customization-finance-systems","Configuration vs Customization in Finance Systems","Configuration fits your process using shipped settings; customization builds bespoke — a permanent liability paid at every upgrade.",1785182339101]