Analytics

From scattered spreadsheets to an analytics layer you can trust.

100+ BI projectsTableau and Data 360Tableau Reseller
Selo Salesforce Authorized Cloud ResellerSelo oficial Salesforce Partner
Authorised resellerTableau is part of the Salesforce ecosystem. We sell the license and deliver the project, with no middleman.

A pretty dashboard with the wrong number is worse than a spreadsheet. We start at the source of the data, model, integration and governance, and only then at the visual.

Talk about BI
Same question, four answersWhat was August revenue?Sales spreadsheetupdated 09/04R$ 4,42MERP reportaccounting closeR$ 4,08MLegacy dashboardno cancelled filterR$ 4,61MLeadership emailrounded numberR$ 4,5Mnone of them is wrong, they measure different thingsAfter the analytics layerAugust revenueR$ 4,21MRULEinvoiced, cancelled excludedSOURCEERP · daily loadOWNERcontrollingsigned off by the teamsOne number, for everyone
Stack

Where we work.

Datago started as a Tableau consultancy in 2018. BI is not an extra line in our portfolio: it is where the company came from.

Tableaudashboards and analysis
Tableau Pulselive metrics
Tableau Prepdata preparation
Databricksprocessing at scale
ETLsource integration
Data warehousea single model
How we structure it

Seven phases, from discovery to publication.

A pretty dashboard with the wrong number is worse than a spreadsheet. That is why the order matters: the visual is the fifth phase, not the first.

DATA LAYERSourcesERP, spreadsheets, CRMETLload and cleanupModeltables and relationsBUSINESS LAYERMetricswhat to measureRuleshow to calculateDashboardshow to show itValidationdoes the number match?Publishingin productionmismatch goes back to the source
Metric dictionary32 metrics with owner, rule and sourceRecognized revenuecontrollingpublishedAverage deal sizesalespublishedMonthly churncustomer successunder reviewMargin per projectfinancepublishedCost per leadmarketingdraftRecognized revenueRULESUM(valor) WHERE status = ganhoAND cancelado = falsoSOURCEERP · daily load at 5 amOWNERControllingUSED IN7 dashboards and 2 targetsREVIEWquarterlysame definition in every dashboardThe rule lives in one place
Phase 1
Discovery

Where the data is born today, who uses it and which numbers do not match. Gathered with the business area, not just with IT.

Phase 2
Sources

Inventory and connection of the origins: ERP, CRM, spreadsheet, database and API. What stays out is also a decision.

Phase 3
Modelling

Data warehouse or lakehouse, dimensional model and the dictionary with the business rules written down.

Phase 4
ETL

Load, treatment and quality routines. This is where the number becomes trustworthy.

Phase 5
Dashboards

Visualisation by audience: the board, the manager and the operation see different cuts of the same truth.

Phase 6
Validation

A check with the area that uses the number. A discrepancy found now costs far less.

Phase 7
Publication

Access governance, publication in Tableau or inside Salesforce, and training for whoever will use it.

PROJECTAnalytics layer on Tableauin progressDiscoverySourcesModelingETLDashboardsValidationPublishedSPRINTSSprint 3 · Dimensional modeldelivered and signed off 08/19doneSprint 4 · Incremental loads3 of 6 tables migratedin progressSprint 5 · Sales dashboardsstarts 10/07scheduledProgress58%EXPECTED PUBLISH28/11Dashboards published9 of 16Sources connected5Open mismatches2One number, for everyone
Follow-up

The data project is visible too.

Every connected source, every load routine and every published dashboard shows in the portal, with hours used alongside.

  • Sources and routines with the status of each load and what is still to connect.
  • Quality measured, not promised: what was treated and what is still open.
  • Dashboards delivered by audience, with sign-off recorded.
  • Hours per line, so the board knows where the effort is going.
See the Doctor portal
Signs the analytics layer is not standing

Too much data, too few indicators.

Sales dashboardupdated at 6 amMONTHLY TARGET82%BY PRODUCT44%NitzapConsult.Tabl.BY REPFUNNELBY MONTHCUMULATIVEDashboard alertAvg. deal size down 9% in the Southeastthree large accounts not renewedOpen in TableauSix views, one source
  • Two departments bring different numbers to the same meeting.
  • The monthly close depends on a spreadsheet only one person knows how to update.
  • The dashboard exists, but nobody opens it because nobody trusts it.
  • Every new question becomes a two-week ticket.
  • The Tableau license is paid for and underused.
  • CRM data and ERP data never match.
CRM and BI under one roof

The advantage of doing both.

Most BI problems in a company using Salesforce sit on the border between the two worlds: a badly modelled field in the CRM becomes a wrong indicator on the dashboard. Because we implement both the CRM and the analytics layer, we fix it at the source instead of patching the dashboard.

See Salesforce consulting

Reportable modelling

The field is designed with the indicator it will feed in mind.

Database quality

Data Mining finds duplicates and gaps before the number reaches the board.

A single supplier

No finger-pointing between the CRM consultancy and the BI one.

Auditable origin

Every indicator has a traceable path back to the source system.

Frequently asked

What people usually ask.

Want to look at your data together?

Tell us which decision is made on gut feeling today. That is where the conversation starts.

WhatsApp +55 27 99997-0276
We already have Tableau, but almost nobody uses it. Can it be recovered?

Yes, and it is usually faster than starting from scratch. The diagnosis normally points to the data model or to a dashboard designed without the business question, rarely to the tool.

Do you work with Power BI or other tools?

Our specialty is Tableau and Data 360, where we have a certified team and a track record. The data layer and the ETL we build serve any visualisation tool.

Do we really need a data warehouse?

Not always. Smaller operations work well with well modelled extracts. The warehouse comes in when there are many sources, high volume, or a need for history the source systems do not keep.

How does the analytics squad work?

A monthly hour bank with an assigned professional, a shared roadmap and priorities set by you. It is the model for continuous demand.

Diagnosis

Let us look at your data.

Tell us which decision is made on gut feeling today. That is where we start.

Rather talk now?

Sales team on WhatsApp, Monday to Friday, 9am to 6pm (BRT).

WhatsApp +55 27 99997-0276