Understanding data science
Blog posts, case studies and whitepapers: Learn more about data science with our expert information. How do I implement data science projects, what does the right IT infrastructure look like and how can I better understand consumer behavior? Find exactly the content you’re looking for and gain insight into best practices in data science across the enterprise.
New customer services with predictive maintenance
Development of a "health indicator" for Schenck Process Europe GmbHWould you like to know more?
Set-up of a analysis environment for REWE International AG
Implementation of a powerful IT infrastructure based on R.Would you like to know more?
Infrastructure consulting, implementation and support for fashion companies
eoda has implemented a high-performance and reliable IT infrastructure for the productive operation of R-analyses for a fashion company.Would you like to know more?
Knowledge transfer workshop: R Shiny apps – Deutsche Bahn Analytics
In a workshop, eoda enabled the DB Analytics team to make analysis results available quickly and attractively with R Shiny.Would you like to know more?
Development of a scoring algorithm for databyte®
eoda supports databyte® in identifying new customer potential.Would you like to know more?
Precise forecasting models – 50Hertz
eoda uses data mining to create reliable forecasting models to compensate for network losses.Would you like to know more?
Predictive maintenance with deep learning
We have developed a deep learning model for a machine builder to reliably predict machine failures.Would you like to know more?
Predictive Maintenance –TRUMPF Lasertechnik
eoda has helped TRUMPF Laser Technology to increase its "Industry 4.0 Maturity Level" based on data and algorithms.Would you like to know more?
Self-learning address database
With its self-learning address database addRess, eoda enables the digital account change service of fino digital.Would you like to know more?
Potentials and opportunities for new business models
An excerpt of a data blueprintWould you like to know more?
New YUNA release!
With version 1.17 new functionalities and features have been enabled in YUNA - Learn more!Would you like to know more?
Online R trainings: Learning data science - live and interactive
Reading time: approx. 2 min. Online concerts, online fitness courses, online yoga - and we also bring our popular R trainings on the internet! Use our online trainings and become an R expert!Would you like to know more?
10 Reasons why YUNA
Reading time approx. 3 min. What are the benefits of YUNA and how can it help you to get started with data analysis? Find out here!Would you like to know more?
Shiny: Performance tuning with future & promises - Part 1
Reading time: approx. 3 min. As analysis apps become more and more complex, the demands on developers to maintain the status quo for performance and availability are also increasing. We take a look at the architecture of the Shiny apps and the packages future & promises!Would you like to know more?
Dear Data Scientists – ease your job!
Reading time: approx. 3 min. You have on the most exciting jobs ever! In the same time you have to meet tremendously high expectations – learn how a data science platform can ease your job!Would you like to know more?
How Shiny and YUNA complement each other
Reading time: approx. 4 min. Shiny® apps have many advantages. In combination with YUNA the advantages are even more enhanced. Learn more!Would you like to know more?
Shiny: Load testing and horizontal scaling
Reading time: approx. 4 min. Learn how detailed load testing can be an important tool to identify and eliminate potential vulnerabilities early enough before the application goes live.Would you like to know more?
Schön‘ juten Tach & Moin Moin: R trainings in Berlin & Hamburg
Reading time: approx. 2 min Data science courses in Berlin and Hamburg - In April and October 2020 we will bring our popular R trainings to major German cities. Become a data science expert with R!Would you like to know more?
How to build data science platforms - Part 5: Data visualization and reliable results
Reading time: approx. 2min. What must be considered when visualizing results and data? We take a look at it!Would you like to know more?
How to build data science platforms - Part 4: Database scalability and business models
Reading time: approx. 2min. This time: Connect various data sources and develop new use cases and entire business models.Would you like to know more?
How to build data science platforms - Part 3: Customizable workflows and dashboards
Reading time: approx. 2min What if the individual project steps were based on the company and individual dashboards could be reused?Would you like to know more?
How to build data science platforms - Part 2: Intelligent user and role concept
Reading time: approx. 2min. Why are users- and role-permissions a factor not to be underestimated in data science platforms?Would you like to know more?
How to build data science platforms - Part 1: UI & Teams
Reading time: approx. 2min. Which factors must be met by modern data science platforms?Would you like to know more?
Version management - The uncomplicated work on a common project
Reading time: approx. 4min. Version management is a central tool for project management. Learn more about how Git can help you work more efficiently on joint projects!Would you like to know more?
Package management: Using repositories in production systems
Reading time: approx. 4min. A good package management in production systems and a fully functional infrastructure are the basis for a complication-free development environment. Learn how to work properly with repositories here!Would you like to know more?
Ansible: Infrastructure as code (IaC)
Reading time: approx. 3min By using Ansible, IT infrastructures can be automated so that manual intervention is no longer necessary. In our article we show you selected examples of how an automated infrastructure configuration can be implemented.Would you like to know more?
Kubernetes: Horizontal scaling of data science applications in the cloud
Reading time: approx. 2 min Due to the constant growth of data and the ever more complex requirements of an IT infrastructure, there are always new challenges for data scientists and data engineers. One possible solution is to combine the RStudio Job Launcher with a Kubernetes cluster: Read our blog article to find out about the advantages!Would you like to know more?
R, Python & Julia in data science: A comparison
Reading time: approx. 3min R, Python or Julia? Meanwhile there are many programming languages, but which one is suitable for your own needs is still unclear. We give you a recommendation!Would you like to know more?
Easy data access: The advantages of a unique database connection with ODBC and DBI
Reading time: approx. 2min Optimum data access is particularly important for the work of data scientists. It enables them to access the relevant data quickly and efficiently.Would you like to know more?
Ei Gude! - Data science courses with R in Frankfurt
Data science courses in Frankfurt! In November it's time: We will bring our popular R-Trainings to Southern Hesse.Would you like to know more?