Djtal

Data

Data migration and quality for Swiss companies

A CRM, a complete ERP, a document management system and any AI system are only as good as their data. We get this foundation right, systematically, before and during every deployment, Zoho included.

In brief

Why do data quality and data migration determine the outcome of a project?

An IT or AI project rests on its data. Djtal, the operational AI specialist for Swiss companies, migrates, cleans and models your data, from a few thousand to hundreds of thousands of records. For the FRC consumer federation, Djtal migrated and cleaned about 100,000 contacts.

Three services

Three ways to invest in the quality of your data.

01

Migration between systems

We extract the data from your current systems (Excel, FileMaker, Access, Salesforce, HubSpot or custom applications), map the data models, migrate in batches and validate. Typical volumes run from a few thousand to several hundred thousand records.

02

Data cleansing and quality

We remove duplicates, standardise formats (addresses, phone numbers, email addresses), correct inconsistencies and enrich records with AI under control. When data is dirty, duplicates skew your figures and the same customer receives two reminders.

03

Modelling and architecture

We design a data model built around your business processes, with a relational schema, integrity rules, access rights and an audit trail. Your team receives a reference document.

The method

How does a data migration work?

  1. 01

    Initial data audit

    Half a day to measure the volume, assess the quality, sketch the target mapping and set out the migration plan.

  2. 02

    Extraction

    The data is exported from your current systems (Excel, FileMaker, Access, Salesforce, HubSpot or a custom application) in a usable format.

  3. 03

    Cleaning

    Deduplication, standardisation of addresses, phone numbers and email addresses, correction of inconsistencies and controlled AI enrichment.

  4. 04

    Migration in batches

    Each batch is loaded into the target system according to the field mapping drawn up, with a quality check at every stage.

  5. 05

    Validation

    Each batch is checked against your live data before the next one starts. You sign it off.

Featured case

For FRC, we migrated and cleaned about 100,000 contacts, companies and deals.

For the Fédération romande des consommateurs (FRC), the consumer federation for French-speaking Switzerland, Djtal overhauled the whole ecosystem: a Zoho One configuration, the migration and cleaning of about 100,000 contacts, companies and deals, and full data integration between the website, the member area, the CRM, support and accounting.

Today the federation runs on a single integrated system. Its data is clean and consistent, around fifty pages of its website are driven by dynamic Creator forms, membership fee renewals are automated and AI enriches its records.

See the FRC case in detail

Pricing and model

CHF 150/hour

excl. VAT · time and materials · CHF 1,200/day

  • Initial data audit · CHF 800 excl. VAT (4 hours, or half a day), covering volume, quality, target mapping and the migration plan.
  • Migration and cleaning are billed on time spent, at CHF 150 an hour, within a budget framework set up front. A fixed-price package is also possible, depending on volume.
  • All prices exclude VAT; 8.1% Swiss VAT is added.

Frequently asked questions

Data migration and quality: what clients ask us.

How large a data migration can Djtal handle in Switzerland?

Djtal migrates from a few thousand to several hundred thousand records. Our clearest example is the migration and cleaning of about 100,000 contacts, companies and deals for the Fédération romande des consommateurs (FRC), with full integration linking the website, the member area, the CRM, support and accounting.

Which systems can you migrate our data from?

Djtal migrates data from Excel, FileMaker, Access, Salesforce, HubSpot or a custom application. We follow the same sequence each time: extraction, data model mapping, migration in batches and validation, with a quality check at every stage.

Why clean your data before an AI project?

Because AI connected to dirty data amplifies its flaws: duplicates skew the figures, reminders go out twice and the model learns from the errors. Cleaning (deduplication, standardised addresses, phone numbers and email addresses, controlled enrichment) comes before any agent deployment.

What does data modelling involve?

Djtal designs a model that follows your real business processes, with a relational schema, integrity rules, access rights and an audit trail. You receive a reference document that your team keeps and maintains.

Before your next project

A scoped migration, validated batch by batch.

An export of your data shows the scale of the job: duplicates, empty fields, inconsistent formats. In half an hour, we put a figure on the cost of putting the data right.

Speak to one of our experts

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