The amount of data that companies produce and process every day is constantly growing. This data contains valuable information about customers, markets, business processes and much more. But how can companies use this data effectively to make better decisions, improve their products and services and tap into new business opportunities?
Our services
- include data science, machine learning, deep learning and generative AI solutions tailored to your specific challenges and goals.
- help you to understand, analyse, visualize and model your data in order to gain insights and derive recommendations for action.
- support you in selecting suitable tools and methods, such as machine learning, artificial intelligence or statistics.
- ensure efficient implementation and seamless integration of data science solutions into your existing systems and processes.
- offer you the right development and operating environment. Both on-prem, in the cloud and responsibly.
- include the selection of the appropriate architecture
Our general approach
We follow a proven approach in our data science projects, which is based on the following steps:
Understanding
We take the time to understand your business objectives, requirements and data sources and formulate a clear problem definition.
Explore
We explore your data using various techniques to understand its quality, structure, patterns and relationships and identify potential questions and hypotheses.
Modeling
We develop and test various data models to answer the most relevant questions and hypotheses and achieve the best results.
Communicating
We present the results of our data analysis to you in an understandable and appealing form, e.g. with dashboards, graphs or reports. We explain the underlying methods and assumptions and give you concrete recommendations for your next steps.
Implement
We support you in implementing data science solutions in your existing systems and processes. We ensure that the solutions are robust, scalable and maintainable and meet your requirements.
Operate
We are also happy to take over the complete operation of your solution and draw your attention to any changes (e.g. model drift, data drift) and suggest optimizations.
Our experts
Our service platforms and technology partners
Additional information
Operationalization of Data Science (MLOps)
Data Science, Artificial Intelligence and Machine Learning
Business Intelligence
Standardized data management creates basis for reporting
Conception of individual Analytics and Big Data solutions
Demand Planning, Forecasting and Optimization
Dashboards & Reports
Common Mistakes in the Development of AI Assistants
8 tips for developing AI assistants
Data Governance
IBM Watson Discovery
IBM Watson Studio
Decision Optimization
IBM Cloud Pak for Data
Talend Real-Time Big Data Platform
IBM Cloud Pak for Data – Test-Drive
Talend Data Integration
IBM Cloud Pak for Data Accelerator
Talend Data Fabric
Data Integration, ETL and Data Virtualization
IBM Watson Knowledge Studio
IBM Watson Assistant
IBM Watson® Knowledge Catalog/Information Governance Catalog
IBM SPSS Modeler
Talend Application Integration / ESB
IBM Cloud Pak for Application
IBM Db2
IBM Cloud Pak for Automation
IBM Netezza Performance Server
IBM InfoSphere Information Server
Big Data, Data Lake & Data Warehousing
State of Fast Feedback in Data Science Projects
Interactive online portal identifies suitable employees
IBM Cloud Pak for Data System
ChatGPT & Co: LLM Benchmarks for September
ChatGPT & Co: LLM Benchmarks for October
Open-sourcing 4 solutions from the Enterprise RAG Challenge
Automated Planning of Transport Routes
IBM Planning Analytics mit Watson
IBM Cognos Analytics 11
Part 2: Detecting Truck Parking Lots on Satellite Images
Part 1: Detecting Truck Parking Lots on Satellite Images
Part 1: TIMETOACT Logistics Hackathon - Behind the Scenes
Creating a Cross-Domain Capable ML Pipeline
Boosting speed of scikit-learn regression algorithms
