For Bucherer, CONSENSO TECH developed a full-stack application for efficiently capturing, normalising and enriching large volumes of product data. Supplier data from Excel, CSV, XML, TXT and PDF is converted into a single unified schema, mapped onto Microsoft Dynamics 365 F&O and prepared for bulk import.
Starting point
Many suppliers with differing data formats and levels of data quality
Regular bulk capture of new collections
Mapping onto the complex data structure of Microsoft Dynamics 365 F&O
A need for consistent product copy across multiple channels and languages
Solution
Full-stack application for bulk product capture
Import and normalisation of Excel, CSV, XML, TXT and PDF
Mapping onto D365 F&O product data structures
User interface for review, editing and approval
AI-assisted product copy generation
Instruction management for channel, language, style, positive and negative lists, and prohibited terms
Result
Faster capture of new product collections
Reduced manual data preparation
Higher data quality and more consistent product information
Scalable copy generation for multiple languages and channels
Better control over tone, style and compliant product communication
For Bucherer, CONSENSO TECH supported the migration of core master data from an Oracle-based legacy ERP database to Microsoft Dynamics 365 F&O. Extensive SQL migration scripts were developed, legacy data was cleansed, and the existing data structures were conceptually mapped onto the new D365 data model.
Starting point
Migration from an Oracle-based legacy ERP database
Complex mapping onto Microsoft Dynamics 365 F&O
Data structures grown over time, with data quality issues
Migration of various master data objects such as customers, suppliers, products and product attributes
A need for repeatable, controllable migration runs
Solution
Development of extensive SQL migration scripts
Extraction and transformation of legacy data
Conceptual mapping onto the D365 F&O data model
Integration of data cleansing steps into the migration process
Structured preparation of the data for import into D365 F&O
Alignment between business departments, data model and technical implementation
Result
Repeatable and controllable data migration
Improved data quality ahead of import into the target system
Reduced manual migration effort
A clear mapping between the legacy data structure and the D365 F&O target model
For Bucherer, CONSENSO TECH developed automated data pipelines with Apache NiFi to synchronise master data daily between the existing legacy system and Microsoft Dynamics 365 F&O. The solution supports international parallel operation, where some legal entities already work in D365 while others continue to be run in the legacy system.
Starting point
Global parallel operation of the legacy system and Microsoft Dynamics 365 F&O
Differing rollout stages per country / legal entity
A need for consistent master data across several system worlds
Recurring daily data transfers
Existing SQL migration logic had to be operationalised
Complex target structures and import logic in D365 F&O
Solution
Construction of automated data pipelines with Apache NiFi
Querying of the legacy database
Reuse of existing SQL migration logic
Transformation of the data into D365-compatible structures
Transfer via the OData batch API of Microsoft Dynamics 365 F&O
Structured, repeatable and traceable synchronisation runs
Result
Consistent master data throughout the international ERP rollout
Support for parallel operation of legacy ERP and D365 F&O
Automated daily data migrations
Reduced manual data transfers
Greater stability and traceability of the data flows
Reusable pipeline structures for further migration work
For DentaCore, CONSENSO TECH designed a modern data platform on Azure. The solution is based on a lakehouse approach with Azure Databricks, structured bronze, silver and gold layers, and Power BI as the reporting and dashboarding layer.
Starting point
Building a scalable data platform on Azure
Structured processing of data from several source systems
A need for clean separation between raw data, cleansed data and reporting models
A foundation for Power BI dashboards and future analytics use cases
An operating and support model for running the platform day to day
Solution
Design of an Azure data platform
Lakehouse architecture with Azure Databricks
Bronze, silver and gold layers for structured data processing
Transformation and harmonisation of source data
Power BI as the reporting and dashboarding layer
Operations, support and further development taken into account
Result
A scalable foundation for reporting and analytics
A clear data architecture with traceable processing steps
Better data quality through structured transformation
Reusable data models for Power BI
A future-proof platform for further BI and analytics requirements
For DPD Switzerland, CONSENSO supported the build of a new data warehouse programme to replace an existing Microsoft BI solution. The new platform is based on an open source stack with a custom-built ETL system, ClickHouse as the BI database, Postgres-based master data management and reusable data models for various reporting tools.
Starting point
Replacing an existing legacy Microsoft BI solution
High operational data volumes in the parcel and logistics business
Many data sources, integrations and stakeholders
Difficulty translating business requirements into technical specifications
A need for a clear roadmap, MVP structure and prioritised use cases
Centralisation and enrichment of master data for BI purposes
Solution
Setting up and structuring the data warehouse programme
Technical requirement engineering for BI, ETL and data modelling
Prototyping of SQL queries, data models and ETL transformations
Custom-built ETL system for data pipelines
ClickHouse as a high-performance BI database for large transaction data volumes
Postgres-based master data management with dedicated master data screens
eMondrian / ROLAP layer for reusable cubes and data models
Use of various analysis and dashboarding tools on the same data foundation
Result
Near-realtime access to operational data
A more consistent reporting and analytics foundation
Better financial and operational transparency
Less manual data maintenance thanks to central MDM
Reusable data models for different BI tools
A cost-efficient platform through targeted use of open source technologies
A foundation for future advanced analytics use cases
For DPD Germany, CONSENSO TECH supports the further development of strategic and operational IT dashboards on an existing Azure-based BI architecture. The focus is on KPI definitions, data source reconciliation, Power BI delivery, data quality checks and close collaboration with business owners and the BI team.
Starting point
An existing, complex Azure BI architecture with hybrid data sources
Differing data sources such as Infor, MDM, Matrix42 and Jira
Strategic and operational dashboards with many KPI definitions
Metrics that were partly manual or unclear
A need for consistent terminology, visualisation and data logic
Close alignment between business owners, the BI team and business departments
Solution
Requirement engineering for strategic and operational IT dashboards
Revision of KPI definitions, units and labels
Data source reconciliation against source systems
Power BI development and dashboard adjustments
Correction of visualisations, colours, labels and drilldowns
Support for detail pages, tooltip and definition logic, and 12-month views
Backlog-based delivery with a clear definition of done per KPI
Result
More meaningful and more reliable IT dashboards
Consistent KPI definitions for management and product teams
Fewer manual reconciliations thanks to clearer data logic
Better transparency over IT performance, costs, HR and delivery metrics
Relief for the internal BI team through focused delivery support
An improved basis for operational and strategic IT steering
For Dr. Wechsler & Partner, CONSENSO TECH developed a modern data warehouse on open source technologies. Data from SwissPension 6 is processed with Apache NiFi, structured in a central Postgres database, stored in MinIO and prepared for Power BI reports.
Starting point
Analysing pension-fund-relevant data from SwissPension 6
Building a structured reporting foundation
Combining person, contract and financial data
A need for a flexible and cost-efficient data warehouse architecture
Making the data available for Power BI analysis
Solution
Building a data warehouse on an open source stack
Apache NiFi for data extraction and ETL processes
Postgres as the central relational database
MinIO as S3-compatible storage
Power BI as the reporting and dashboarding layer
Structuring of pension-fund-relevant data from SwissPension 6
Result
A central data foundation for pension fund reporting
Better analysis of person, contract and financial data
A flexible open source architecture
Reusable data models for Power BI
A basis for more transparent operational and strategic analysis
For EliteGo, CONSENSO TECH developed a data pipeline for the automated preparation of FINMA-relevant broker data. Policy, customer, insurance and commission data is consolidated and visualised in a Power BI dashboard for annual reporting.
Starting point
Annual reporting obligations for insurance intermediaries
Consolidating broker data from different sources
Preparing policies, customers, insurance classes and commissions
Distinguishing between new and existing policies
A need for traceable metrics for FINMA-relevant reporting
Reducing manual data preparation
Solution
Building an automated data pipeline
Import and structuring of insurance, policy and customer data
Preparation by FINMA-relevant category
Consolidation of commissions, brokerage fees and other remuneration
Power BI dashboard for analysis and reporting
Analysis by insurer, customer category, insurance class, existing versus new business, and over time
Result
Faster and more structured annual FINMA reporting
Better transparency over policies, customers and commissions
A reusable reporting foundation instead of manual one-off analysis
Greater traceability of the metrics
A management overview of broker activity and income
For ESCMID, CONSENSO implemented an interface between Odoo and Abacus. Operational congress processes, sponsorship, contract management and invoicing are represented in Odoo, while Abacus is connected as the central finance system. Invoices are transferred and payment status updates are synchronised back into Odoo.
Starting point
Odoo as the operational system for congress, sponsorship and CRM processes
Abacus as the central finance system
Invoicing in Odoo, accounting treatment in Abacus
A need to feed payment status back into Odoo
Transparency over open items for sales and operational teams
Reducing manual reconciliation between Odoo and accounting
Solution
Implementation of an Odoo-Abacus interface
Transfer of Odoo invoices to Abacus
Synchronisation of payment status from Abacus back to Odoo
Mapping of invoice and payment logic between the operational system and the finance system
Support for congress processes around sponsorship, contracts and invoices
Result
An end-to-end process from sponsorship and CRM through to financial accounting
Less manual reconciliation between Odoo and Abacus
Better transparency over paid and outstanding invoices
Up-to-date payment information directly available to sales and operational teams
A more stable foundation for professional congress management
For Handel Schweiz, CONSENSO TECH took on the data migration workstream as part of the Abacus ERP implementation. Data from the existing Sage system was transferred automatically, cleansed, and optimised both conceptually and technically for the new Abacus structure.
Starting point
Migration from Sage to Abacus
Master data structures grown over time
Data quality issues in the legacy data
A need for automated data transfer
Conceptual adaptation to the new Abacus data structure
A clean foundation for invoicing, reporting and ERP operations
Solution
Taking on the data migration workstream
Automated data transfer between the legacy system and Abacus
Cleansing and preparation of legacy data
Conceptual and technical optimisation of the data structure
Preparation of the data for productive operation in Abacus
Result
A structured migration from Sage to Abacus
Improved data quality in the new ERP system
Less manual migration effort
A better foundation for reporting, invoicing and operational processes
For Handel Schweiz, CONSENSO TECH developed a small application for intelligent duplicate detection in address and contact data. A vector-based approach identifies not only exact duplicates but also similar spellings, abbreviations and differing contact details.
Starting point
Duplicates in company addresses and contacts
Differing spellings, typos, abbreviations and additional information
Standard functions often detect only exact matches
Data quality is critical for invoicing and reporting
Manual duplicate detection is time-consuming and error-prone
Solution
Concept and prototype for intelligent duplicate detection
Vector-based comparison of address and contact data
Use of TF-IDF and cosine similarity
Assessment of potential duplicates using similarity scores
A foundation for UI-supported cleansing, reports and data quality dashboards
Flexible thresholds and weightings for different data quality rules
Result
Better detection of non-obvious duplicates
Higher data quality in address and contact records
Less manual checking effort
A more reliable foundation for invoicing and reporting
For Kuhn Design, CONSENSO TECH developed an automated data migration to provide up-to-date data from the legacy system regularly during the ongoing Odoo implementation. Test data could therefore be refreshed continuously, migration logic validated early and go-live risk reduced.
Starting point
A multi-month Odoo implementation while the legacy system remained in use
Continuous changes in master data and operational data
A need for current test data during configuration and validation
The risk of a late or one-off go-live migration
The need to test and improve migration logic early
Solution
Building an automated data migration from the legacy system into Odoo
Repeatable migration runs during the implementation phase
Regular refreshing of test data
Early validation and optimisation of the migration logic
Preparation of a controllable go-live migration process
Result
Current test data throughout the implementation
Early detection of data and mapping problems
Reduced go-live risk
Less manual effort to provide test data
Better quality assurance for the Odoo rollout
A more stable foundation for the productive system change
For Lotti Partner AG, CONSENSO TECH developed a calculator to automate the quotation process. The solution processes SIA/CRBX files, draws on historical reference data and NPK catalogue information, calculates plausible unit prices and exports the costed quotation back for import into SORBA.
Starting point
High manual effort across 600 to 1,000 quotations per year
Dependence on the experience of individual people
Complex SIA/CRBX and NPK-based quotation logic
Incorrect or incomplete reference data leads to incorrect costings
Export to and import from SORBA has to work reliably and without rounding differences
A need for traceable, plausible and verifiable costing proposals
Solution
Feasibility study on automating the quotation process
Web application with upload and costing logic
Processing of CRBX/SIA files and PDF context
A standardised internal schema for quotation data
Use of historical reference data and NPK catalogues
Minimum price logic and a confidence indicator
Import history and quotation history
Validation of missing NPK catalogues
Export of the costed quotation for SORBA
Result
Reduced manual costing work
Experience-based knowledge preserved within the quotation process
More plausible and more traceable quotation costings
Reliable SIA/CRBX export and import into SORBA
A better overview of reference data and earlier costings
A foundation for further AI-supported quotation automation
For Nateco, CONSENSO TECH developed a web application for structured searching and filtering of suitable tree and shrub species. Plant lists are converted into a digital data model and made searchable through a mobile- and desktop-capable interface using criteria such as origin, suitability for streets, region, growth height and biodiversity.
Starting point
Specialist plant information existed in complex Excel lists
Many criteria had to be presented in a structured, filterable and understandable way
Different audiences need quick access to suitable species
Desktop and mobile use both had to be supported
Specialist data had to be converted into a consistent digital data model
Solution
Extraction and normalisation of the plant lists
Construction of a structured JSON/JavaScript data model
Web application with search, filtering and sorting
Filters for origin, suitability for streets, region, growth height and biodiversity
Detail views with site requirements and additional specialist information
CSV export of the filtered results
Responsive UI for desktop and mobile
Result
Fast access to suitable tree and shrub species
Better usability of complex specialist data
Site-appropriate selection based on transparent criteria
A mobile- and desktop-capable application
A reusable digital data model
A foundation for further specialist extensions and data quality improvements
For ORIS, CONSENSO developed an interface between ProConcept and Odoo. Because certain business functions continue to run in the legacy system ProConcept, deliveries from ProConcept are processed automatically in Odoo and created as purchase orders for subsidiaries. Product master data, including complex tree structures, is synchronised at the same time.
Starting point
Parallel operation of ProConcept and Odoo
Certain business functions remain in the legacy system
Automatic creation of purchase orders in Odoo
Synchronisation of product master data
Handling of complex tree structures
Support for international subsidiaries
Solution
Development of an interface between ProConcept and Odoo
Automated processing of delivery data from ProConcept
Creation of Odoo purchase orders for subsidiaries
Synchronisation of relevant product master data
Mapping of complex product and tree structures
Support for the international Odoo rollout
Result
End-to-end processes between the legacy system and Odoo
Less manual entry of purchase orders
Consistent product master data across system boundaries
More stable operational processes for subsidiaries
For Paul Ullrich, CONSENSO TECH developed automation for product data and inbound email orders. Supplier factsheets in Word, PDF, Excel and CSV are converted into a product schema, enriched with multilingual product copy and prepared for ERP import. Inbound order emails are also translated automatically into ERP orders.
Starting point
Product factsheets in many formats such as Word, PDF, Excel and CSV
Differing data quality and structure per supplier
A need for a uniform product schema for ERP import
Multilingual product copy for different websites and tasting contexts
Regulatory or communication requirements, for example prohibited terms for spirits
Manual processing of inbound order emails
Solution
Automated extraction of product information from supplier factsheets
Normalisation into a uniform product schema
Generation of multilingual product copy
Rule-based control of copy, terminology and channels
Preparation of structured records for ERP import
Automation of inbound email orders
Translation of inbound orders into ERP orders
Result
Less manual effort in product data maintenance
More consistent product information across channels and languages
Faster onboarding of new products into the ERP
Compliant product copy for sensitive product categories
Automated order capture from email orders
A scalable foundation for further AI and process automation
With DataFlow ProX, CONSENSO TECH developed a modular platform for the automated processing of product data. Data from Excel, CSV, PDF, ERP, web or API is imported, structured, enriched and passed to target systems such as ERP, shop, CRM or PIM through intelligent export and interface logic.
Starting point
Product data spread across many formats and systems
High manual effort for import, cleansing and enrichment
Differing data quality by source or supplier
A need for reusable export formats and interfaces
Consistent product information for ERP, web shop, marketing and further channels
A scalable foundation for AI-supported product data processes
Solution
Modular product data platform
Import from Excel, CSV, PDF, ERP, web and API
AI-supported pre-processing and analysis
Structuring, standardisation and redundancy checking
Automatic addition of technical data, attributes, copy and images
SEO- and marketing-optimised product data
Connect and export logic to ERP, shop, CRM, PIM and further systems
AI agent capabilities for search, advice, automation and data queries
Result
Automated product data processes from import through to export
Higher data quality and more consistent product information
Less manual preparation by business departments
Faster product availability in target systems
Reusable data and integration logic
A foundation for AI-supported search, advice and process automation
For SCS IT / Linard, CONSENSO TECH developed an application to automate daily supplier data. Product catalogues, prices and stock levels from various supplier files are processed, transformed and made available for ERP and eCommerce processes.
Starting point
Daily product and stock data from several IT hardware suppliers
Differing file formats, currencies and data structures
Manual preparation for ERP and eCommerce
A need for dynamic pricing logic and promotion capability
Updating existing products and capturing new items
Handling product conditions such as NEW, REF, USED, RENEW or OEM-compatible
Duplicate and deletion logic per supplier
Solution
Development of an application for supplier data import and export
Processing of multiple supplier files
Combination with ERP product data from OPACC
Support for CHF, EUR and GBP including exchange rate logic
Mapping onto defined export structures
Rules for price mark-ups, minimum prices and product conditions
Data validation, editing and deletion logic
User interfaces for import, validation, configuration and export
Preparation of export files for the ERP and eCommerce platform
Result
A significant reduction in manual data preparation
Up-to-date product prices and stock levels
Faster onboarding of new products
Better control of pricing logic and promotions
Higher data quality through validation and mapping
A foundation for further automation, for example FTP processing or additional product data sources
For volenergy, CONSENSO TECH developed a monitoring concept and an operational monitoring solution for business-critical interfaces between Microsoft Dynamics 365 F&O and the legacy system OASE. Using Grafana and Apache NiFi, data flows, interface servers and transfer errors were made more transparent and more controllable.
Starting point
D365 F&O as the new finance system, OASE still in use as the operational system
Business-critical bidirectional interfaces
Stability problems after go-live
A lack of transparency over interface servers and data transfers
A need for operational control for the finance team
Interfaces partly based on older technical structures
Solution
Analysis of the existing interface landscape
Development of a monitoring concept
Monitoring solution with Grafana and Apache NiFi
Monitoring of interface servers and data flows
Visibility of successful and failed data transfers
Reconciliation and control mechanisms for relevant financial data
Advice on stabilising and developing the technical stack
Result
Better transparency over business-critical interfaces
Earlier detection of errors and outages
More control for the finance team
More stable data flows between D365 F&O and OASE
Reduced operational risk after go-live
A foundation for structured interface and operations monitoring
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