Our current projects
We have compiled projects for you in the areas of data migration, database administration, and data engineering & data science.
Sub-project Data Transfer ERP Migration
Data transfer from the existing, in-house further developed ERP system to Microsoft Dynamics365 (Finance & Operations).
• Analysis of the existing data structures in the source system (Oracle database, Azure VM)
• Defining the entity / field mappings (target structure specified by MS D365)
• Transformation of the information from the existing to the new process flows
• Re-encoding of code fields / tables
• Data export to Excel (D365 specification)
• Import into the target structures via Data Management Framework from D365 (Azure)
Former projects
We have put together a selection from the various areas for you so that you get an overview of our expertise.
Data migration
Datacenter Consolidation
Migration of the MS SQL Server databases from the three on-prem data centers to the private cloud.
• 36 SQL server instances, approx. 150 databases.
• DB sizes from 2 GB to 21 TB
• Version upgrade from 2008r2 / 2012 to 2016
• Completely new authorization concept
• Reconfiguration of the ETL systems
• Migration on 2 weekends without interruptions to the ETL routes
• Project duration 7 months
Complete coordination and technical implementation of the migrations of more than 40 MSSQL servers and over 150 databases to the latest version.
The goal was to make the database infrastructure future-proof, optimize performance and increase security.
The core tasks included:
• Inventory and analysis
• Comprehensive analysis of the existing MSSQL server landscape, including the identification of outdated systems, dependencies and critical databases
• Development of a detailed migration plan based on the specific requirements of the systems and applications
• Planning a migration concept for a smooth transition and ensuring minimal downtime
• Technical implementation:
• Execution of the migrations including test and validation phases
• Implementation of new security features and performance optimizations
• Close collaboration with various specialist departments to ensure that all functional and operational requirements are met
• Performing tests after the migration to check the functionality and performance
Development of a data migration framework
A framework for data migration from third-party systems (in-house and external) was developed for the manufacturer of a widely used point of sales system in the healthcare environment.
The following requirements had to be covered here
• Industrialization of data transfer
• Traceability to the source system
• Support for various source systems
• Support for various source formats (DBMS, file-based)
• Possibility for data quality checks
• Multi-client capability
MS Dynamics 4.0 replacement
In the course of replacing an MS Dynamics 4.0 CRM system with a new in-house developed CRM system, the data transfer and data integration of the new system had to be developed in the final phase of the project.
The following challenges arose here:
• very tight time window for implementation of only 10 weeks
• previous multiple postponements of the GoLife
• Missing documentation of the source system, the data volume to be migrated, and the data model of the target system
• Target system was continuously developed into a release candidate
• Integration into existing peripheral systems including area allocations of existing and target customers to field staff
• Parallel operation of both CRM products
Database administration
Development of a comprehensive PowerShell module for the automation of all administrative tasks related to MSSQL servers.
The goal of this project was to automate and standardize recurring administrative tasks related to MSSQL servers, increase efficiency, and minimize human error. The developed PowerShell module was used both for the initial setup of new MSSQL instances and for ongoing operation. It includes a variety of processes that have been automated in different areas of database management.
The main functions of the module include:
• Information query: Retrieving detailed information about databases and instances
• Database encryption: Activation and deactivation of database encryption
• Backup management: Automated creation of backups for databases
• Configuration management: Configuration and optimization of database settings according to the specified operating standards
• Database migration: Performing database migrations between instances
• Database management: Creation and deletion of databases
• SQL updates: Execution of SQL updates on one or more instances
By implementing this module, the administrative processes could be significantly accelerated and standardized, which saves both time and resources and significantly reduces the error rate.
Data Engineering & Data Science
Optimization of an existing machine learning model for logistics forecasting based on weather data.
The original model, developed in R and Python, had accuracies of 60–80% and required thorough review and adjustment. The data preparation was completely revised in Python, aggregations, enrichments and cleanups were carried out and irrelevant features were removed to make the model leaner and more precise. In addition, the data distribution was optimized to achieve a more balanced data distribution. With targeted adjustments to the classifier and the parameters, the prediction accuracy could be increased to over 90%, thus creating a much more precise basis for decision-making processes.