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How We Work

Data modernization services: you set the goal, we design and implement it

Data modernization services that start from a business goal, then design and build the pipelines, data model and dashboards needed to reach it.

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One governed warehouse cuts month-end close from 12 days to 4ERP, CRM and spreadsheet data flow into one governed warehouse; the dashboard shows close time falling from 12 to 4 days over six months (demo data).Goal: close the books in days, not weeksERPCRMSpreadsheetsGoverned warehouseMonth-end close4 dayswas 12 daysDays to close, last 6 monthsDemo dataOne governed warehouse cuts month-end close from 12 days to 4Mobile view: ERP, CRM and spreadsheets feed one governed warehouse; month-end close falls from 12 to 4 days (demo data).Goal: close the books in days,not weeksERPCRMSpreadsheetsGoverned warehouseMonth-end close4 dayswas 12 daysDays to close, last 6 monthsDemo data

Our data modernization services are run as defined strategy and implementation projects, proposed once your organization is ready. You name the outcome, such as a faster month-end close or one view of revenue. We confirm fit, then own the design, build and handover.

Challenges we solve

When month-end takes days, the data stack is the bottleneck

The warning signs are usually visible to leadership before anyone calls it a data problem.

Copying figures by hand takes almost half of month-endSorted horizontal bars: copying figures 46 hours, reconciling 22, waiting for the analyst 14, fixing connections 10, formatting 8.Copying figures by hand takes almost half of month-endManual hours per month-end close, by task (demo data)Demo dataCopying figures from ERP, CRM andspreadsheets46 hReconciling two revenue versions22 hWaiting for the one analyst14 hFixing broken connections10 hFormatting the report pack8 hCopying figures by hand takes almost half of month-endMobile view: Sorted horizontal bars: copying figures 46 hours, reconciling 22, waiting for the analyst 14, fixing connections 10, formatting 8.Copying figures by hand takes almosthalf of month-endManual hours per month-end close, by task (demo data)Demo dataCopying figures from ERP, CRM and spreadsheets46 hReconciling two revenue versions22 hWaiting for the one analyst14 hFixing broken connections10 hFormatting the report pack8 h

Month-end reports take days, because figures are copied by hand from the ERP, CRM and spreadsheets. Two departments bring different revenue numbers to the same meeting, and nobody can say which is right. Legacy systems hold critical data but cannot connect to modern reporting tools. Every new question goes to the one analyst who knows where the data lives, and that person is now a bottleneck. Connections between systems break without warning, and errors are found by customers or auditors instead of your team.

AI and automation projects stall too. The pilot looks promising, then cannot scale, because the data behind it is incomplete or locked away.

If two or three of these apply, your data is limiting decisions instead of supporting them. A modernization project is worth scoping before another round of manual fixes.

Data maturity self-check

Is your data stack holding the business back?

7 questions on common data practices. The result is an illustrative level, not a benchmark score.

Illustrative
1. How long does month-end reporting take after the books close?
2. How do figures move from the ERP and CRM into reports?
3. Do departments bring the same revenue number to meetings?
4. Who can answer a new data question?
5. How are broken connections between systems found?
6. Can older systems feed modern reporting tools?
7. What happened to your last AI or automation pilot?
0 of 7 answered
What it is

Data modernization replaces manual workarounds with one reliable platform

Data modernization moves a business from scattered, manual data work to one connected and automated data infrastructure. It usually covers four things: connecting source systems, a central data warehouse (one store for clean, combined data), a shared data model with agreed definitions, and automated reporting.

Four manual workarounds become one platformFour rows, each pairing a manual workaround with its modern replacement: connectors, warehouse, shared model and automated reporting.Four manual workarounds become one platformThe four components, before and afterManual workaroundModernized platformSourcesExports emailed by handScheduled connectors to eachsystemStorageSpreadsheets on shared drivesOne central data warehouseDefinitionsEach team has its own revenueOne shared data model withagreed definitionsReportingRebuilt by hand every monthRefreshed automaticallyFour manual workarounds become one platformMobile view: Four rows, each pairing a manual workaround with its modern replacement: connectors, warehouse, shared model and automated reporting.Four manual workarounds become oneplatformThe four components, before and afterSourcesManual workaroundExports emailed by handScheduled connectors to each systemStorageManual workaroundSpreadsheets on shared drivesOne central data warehouseDefinitionsManual workaroundEach team has its own revenueOne shared data model with agreeddefinitionsReportingManual workaroundRebuilt by hand every monthRefreshed automatically

Done well, it is data transformation consulting with a clear business purpose. It is not an IT migration for its own sake or a tool swap. The test is simple: after the project, can leaders make the decision they named at the start, faster and with more confidence?

Benefits

Modernized data gives the CEO, CFO and data lead faster, safer decisions

For the CEO, modernized data means one trusted view of performance across business units and regions.

It is available on demand, not at the end of the month. It also gives AI plans a foundation that can actually be delivered.

Each leader sees the gain in their own termsThree tiles: CEO daily view, was month-end; CFO 6 reconciliations a month, was 40; data lead 2 broken connections a quarter, was 14.Each leader sees the gain in their own termsOne measure per role after modernization (demo data)Demo dataCEODailyperformance view acrossunits and regionsWas: month-end onlyCFO6manual reconciliations permonthWas: 40Data or IT lead2broken connections perquarterWas: 14Each leader sees the gain in their own termsMobile view: Three tiles: CEO daily view, was month-end; CFO 6 reconciliations a month, was 40; data lead 2 broken connections a quarter, was 14.Each leader sees the gain in their owntermsOne measure per role after modernization (demo data)Demo dataCEODailyperformance view across unitsand regionsWas: month-end onlyCFO6manual reconciliations permonthWas: 40Data or IT lead2broken connections per quarterWas: 14

For the CFO, it means a faster close and fewer manual reconciliations. Margin and cash reports become reliable. Audit questions are answered from documented pipelines instead of spreadsheets. And technology spend links clearly to the decisions it improves.

For the data or IT lead, it means fewer fragile connections and a platform the team can extend without rebuilding it every year. Each group sees results in its own terms. That is what keeps a project funded and supported to completion.

One trusted view of performance, on demand

Results across business units and regions are available when needed, not at the end of the month.

  • One view across units and regions
  • A foundation AI plans can actually use
  • Decisions made on current data
Services

Our data modernization services cover every layer, from source systems to dashboards

Hiring several data consulting firms, one per layer, adds handoffs. We combine the data management consulting services each project needs in one team. That means fewer handoffs, and one owner accountable for the result from start to finish.

One team covers every layer of the data stack, so no handoffsIsometric stack of five layers, sources, integration, warehouse, BI and automation, with governance spanning them and each service attached to its layer.Sources5CRM cleansing and quality rulesIntegration2Pipelines move data automaticallyWarehouse2One governed storeBI3Dashboards and self-serviceAutomation4Zapier, Make or n8n workflowsGovernance spans every layer1Strategy and architecture set the target designOne team covers every layer of the data stackMobile view: five layers from sources to automation, each with the service that covers it, and governance across all of them.1Strategy and architecture setthe target designGovernance spans every layerAutomation4Zapier, Make or n8n workflowsBI3Dashboards and self-serviceWarehouse2One governed storeIntegration2Pipelines move data automaticallySources5CRM cleansing and quality rules
data strategydata integrationbusiness intelligencebusiness process automation
What you get

You own every asset the project produces

Every data analytics project ends with concrete assets your team owns outright. We charge no license fee for what we build, and there is no lock-in.

Every asset the project produces is owned by your teamFive asset cards, architecture diagram, data model, monitored pipelines, dashboards and runbooks, each with the question it answers, all marked as yours.ArchitecturediagramHow does itfit together?YoursDocumenteddata modelWhat does revenuemean here?YoursMonitoredpipelinesDid last night'sload run?YoursExecutivedashboardsAre we closerto the goal?YoursRunbooks anddata dictionaryCan we run itwithout help?YoursOwned by your team: no license, no lock-inYour team owns all five project assetsMobile view: five deliverables, each answering a question your team can now handle alone.Architecture diagramHow does it fit together?YoursDocumented data modelWhat does revenue mean here?YoursMonitored pipelinesDid last night's load run?YoursExecutive dashboardsAre we closer to the goal?YoursRunbooks and data dictionaryCan we run it without help?YoursOwned by your team:no license, no lock-in

  • Explain the system to anyone

    A target architecture diagram shows sources, pipelines, warehouse and reports, with the reason for each choice.

  • Use one definition of revenue

    A documented data model sets agreed definitions for every core metric.

  • Know when something breaks

    Automated pipelines are monitored and send alerts when a load fails.

  • See progress against the goal

    Executive and operational dashboards track the outcome you set at the start.

  • Run it without us

    Runbooks, a data dictionary and handover sessions prepare your team to maintain and extend it.

How we work

Five reviewed steps take a data modernization project from goal to handover

Every project follows the same five steps, and it starts with advice, not a build. We first agree the outcome and check fit and readiness. If your data, team or priorities are not ready, we say so and continue with advisory, an assessment or training instead. Each step ends with a review and your sign-off, so nothing moves forward without your approval.

Five reviewed steps from goal to handover

Select a stage, use Next or the arrow keys

Agree the outcome. You state the business goal. We advise on success measures, systems in scope and constraints.

Step 1 of 5

After the check, the order follows the project: design, build in reviewed rounds, a visible outcome, and training so your team owns the result.

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Sample views

Three samples show the finished result on demo data before you commit

We show what a finished project looks like before you sign. The matrix below compares our three samples, built on demo data only: executive performance, financial reporting and operations.

Three samples show what you get before you signMatrix of three sample dashboards by KPIs, sources joined, refresh and the decision each supports.Three samples show what you get before you signThe sample set we walk through in the first consultation (demo data)SampleKPIsSources joinedRefreshDecision it supportsExecutiveperformanceRevenue, gross margin,operating cash flowERP, CRMDailyWhich region needsattentionFinancialreportingDays to close, manualjournals,reconciliation gapsERP, generalledger, bankfeedsDailyWhere the close loses timeOperationsOn-time delivery, ordercycle time, backlogERP, warehousesystemDailyWhere to cut costThree samples show what you get before you signMobile view: Matrix of three sample dashboards by KPIs, sources joined, refresh and the decision each supports.Three samples show what you get beforeyou signThe sample set we walk through in the firstconsultation (demo data)Executive performanceKPIsRevenue, gross margin, operating cash flowSources joinedERP, CRMRefreshDailyDecision it supportsWhich region needs attentionFinancial reportingKPIsDays to close, manual journals, reconciliationgapsSources joinedERP, general ledger, bank feedsRefreshDailyDecision it supportsWhere the close loses timeOperationsKPIsOn-time delivery, order cycle time, backlogSources joinedERP, warehouse systemRefreshDailyDecision it supportsWhere to cut cost

For each sample it lists the KPIs, the sources it joins, how often it refreshes and the decision it supports, such as which region needs attention or where to cut cost. We walk through the samples live in the first consultation and discuss which views fit your goal, before any work starts on your own data.

Platforms we use

Platform-neutral advice means the stack fits your team, not a sales target

We hold no vendor resale targets, so recommendations follow fit, cost and your team's skills.

The stack is chosen on fit, cost and skills, not a sales targetPlatforms grouped by role, BI, CRM, ERP and finance, automation, web and ops data, feeding one stack chosen on fit, cost and team skills. Names only, no logos.BI and reportingPower BICRMHubSpotSalesforceZohoERP and financeNetSuiteOdooQuickBooksAutomationZapierMaken8nWeb and ops dataGA4AirtableYour stackChosen on fit, cost and team skillsPlatforms are grouped by role and chosen on fitMobile view: platforms grouped by role feed your stack, chosen on fit, cost and team skills.BI and reportingPower BICRMHubSpotSalesforceZohoERP and financeNetSuiteOdooQuickBooksAutomationZapierMaken8nWeb and ops dataGA4AirtableYour stackChosen on fit, cost and team skills
HubSpotImplementation, reporting and CRM dataSalesforceSalesforce reporting, dashboards and integrationPower BIPower BI dashboards and developmentGoogle Analytics 4GA4, tracking and attribution set up rightERPNetSuite, Odoo and Zoho implementation and reportingQuickBooksQuickBooks reporting, forecasting and integrationAirtable, Zapier, Make & n8nNo-code automation with Airtable, Zapier, Make and n8n

For BI and reporting we work mainly in Power BI. For CRM data we work with HubSpot, Salesforce and Zoho. For finance and ERP we connect NetSuite, Odoo and QuickBooks. Airtable supports lightweight operational data. Zapier, Make and n8n handle process automation. Web and marketing data comes from GA4.

For growing data volumes, we design scalable pipelines. Where a cloud migration is part of the goal, we pick a cloud warehouse based on your current stack, data volumes, budget and the skills your team already has or plans to hire.

We deliver remotely to teams in the US, the UAE and elsewhere.

Pricing

Fixed scopes mean you know the cost before work starts

Unlike open-ended, hourly data analysis consulting services, our projects are priced on a fixed scope agreed in writing, once the readiness check confirms that a project is the right step.

How projects are scoped

Four drivers set a fixed scope before work startsDriver tree: source systems, data model, dashboards and handover feed a fixed scope of an 8-week first phase, demo data.Four drivers set a fixed scope before work startsA worked example of a first phase (demo data)Demo dataFixed scope and price: 8-weekfirst phaseAgreed in writing; typical first phases run 6to 12 weeksSource systems5 to connectData model1 shared modelDashboards4 requiredHandover2 training sessionsFour drivers set a fixed scope before work startsMobile view: Driver tree: source systems, data model, dashboards and handover feed a fixed scope of an 8-week first phase, demo data.Four drivers set a fixed scope beforework startsA worked example of a first phase (demo data)Demo dataSource systems5 to connectData model1 shared modelDashboards4 requiredHandover2 training sessionsFixed scope and price: 8-week firstphaseAgreed in writing; typical first phases run 6 to12 weeks

Four things drive the scope: the number of source systems, the complexity of the data model, the dashboards required and how much handover your team needs. A first phase typically runs 6 to 12 weeks (typical, depends on scope).

Large programs are split into phases. Each phase has its own deliverables and sign-off, so you can pause or adjust after any of them. Support after go-live is optional, as advisory or a monthly embedded data team.

Frequently asked questions

Data modernization services: questions buyers ask before they commit

How is this different from hiring analytics consulting firms for reports?

Report-only work sits on top of the data you already have. A data modernization project fixes the foundation first: the connections, the data model and the rules. So reports stay accurate after the consultants leave. The goal is a platform your team owns, not a long-term reliance on outside analysts.

Do we have to replace our current systems?

Rarely. Our data modernization services usually keep the ERP, CRM and finance systems you already use, and connect them properly. We suggest replacing a system only when it cannot provide the data your goal needs. If so, we explain the cost, risk and trade-off clearly before any decision is made.

Can the project prepare us for AI?

Yes. Clean, connected and governed data is a core requirement for useful AI. A common starting point is an AI readiness assessment, which shows the gaps. A modernization project then runs to close those gaps in priority order, so AI use cases can move from pilot to everyday use.

AI readiness assessment
Contact form

Tell us the goal; we will advise on the right first step

Describe the outcome you want, the systems involved and any deadline. We reply within one business day. In a short call we confirm whether a project is the right first step. If it is, we propose a scope, approach and next steps; if it is premature, we say so and recommend advisory, an assessment or training. If you already have a brief, send it along. Book a consultation to start.

Send the goal, get advice on the right first step, then decideThree steps after you send the form: you send the goal, we advise and check fit within one business day, you decide the right first step.WHAT HAPPENS NEXT1You send the goalOutcome, systems and deadline2We advise and check fitReply within one business day3You decideRight first step, scope and approach
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