The data science blog by eoda
The data analysis blog from the data science specialist: We tell you stories about the data science languages R and Python, data science in a business context and much more.
New YUNA release!
In version 1.20 we have set course developing a new feature - Learn more!
08.09.2020
Data Science Framework - YUNA elements now available for download!
reading time: approx. 1min. Our new data science application is now available as a direct download! Test it now 30 days free of charge – no strings attached!
13.08.2020
Reasons why data science projects are not always successful - Part 1
Reading time: approx. 3min. Why does it happen that data science projects do not bring the success that one expects after long planning? We will shed light on some factors!
27.05.2020
RStudio Team Admin Training - Remotely
Reading time: approx. 2 min. We train you in RStudio Server Pro, RStudio Connect and RStudio Package Manager – remotely. Register now for our online training in June 2020.
14.05.2020
Online R trainings: Learning data science - live and interactive
Reading time: approx. 2 min. In our two most popular courses "Introduction to R" and "Machine learning with R" we provide you with the knowledge you need for the productive use of R - remotely. Register now.
14.05.2020
Shiny: Performance Tuning with future/promises
Reading time: approx. 4 min.In our practical blog post we show with the help of an example app how future/promises apps can be kept reactive despite complex tasks. Try it yourself with the code we provide and put theory into practice!
16.04.2020
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!
26.03.2020
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!
24.03.2020
Shiny: Performance tuning with future & promises - Theory
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!
19.03.2020
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!
11.03.2020
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!
04.03.2020
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.
30.01.2020
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!
22.01.2020
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!
15.12.2019
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.
10.12.2019
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?
08.12.2019
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?
06.12.2019
How to build data science platforms - Part 1: UI & Teams
Reading time: approx. 2min. Which factors must be met by modern data science platforms?
03.12.2019
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!
28.11.2019
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!
21.11.2019
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.
14.11.2019
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!
23.10.2019
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!
16.09.2019
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.
04.09.2019