Different sources.
One consistent dataset.

Connect spreadsheets, ERP, CRM, and databases. Standardize information and monitor quality before the numbers reach your reports.

Connected data

Every source preserved. Every exception with a reason for review.

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From context
to solution.

01 / The problem

Where work gets stuck.

Sales, inventory, and finance use different codes and formats. Duplicates and empty fields are mixed in with records ready for analysis.

02 / The approach

How the project addresses it.

Data preparation applies explicit rules for formatting, required values, and duplicates. Validated records are ready for use; unresolved issues remain traceable.

03 / Validation

What needs to be checked.

Check input and output counts, verify relationships, and ensure exceptions are not discarded without a record.

What your project
can include.

01

Source connections

Map access options and integrate through files, APIs, or database queries.

02

Preparation and standardization

Rules for codes, dates, records, required fields, and duplicates.

03

Quality and refresh

Validate data loads, log unresolved issues, and document transformations.

Clear steps.
Shared decisions.

  1. 01

    Understand the sources

    Inventory fields, refresh frequency, and relationship keys.

  2. 02

    Apply the criteria

    Standardize information using documented rules.

  3. 03

    Check the data load

    Validate volumes, relationships, and exceptions before use.

Common questions.

Can you connect my ERP or CRM?

I assess the system’s export, API, and database access options, along with the permissions required.

Is incorrect data deleted?

Data preparation should preserve traceability. Unresolved issues can be set aside for review, following the rules defined with the team.

Could a similar project
work for you?

Tell me how your operations work and what you would like to improve.

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