Information Systems

Many companies are increasingly focusing their business models on the use of primarily existing but unused data. Together with you, we develop individual solutions to uncover your "gold". We support you in analyzing your data and building a toolchain for the automized analysis of your data.

The migration of existing data into a new system is often a challenge not to be underestimated. We bring our expertise to your migration projects and create customized solutions for your requirements.

With professional support ...

  • you receive hands-on support when setting up your 'Big Data' environment
  • you get a grip on your ALM tools
  • you access extensive methodology and technology know-how
  • you introduce cutting-edge methods and professional tools in your development
  • you secure the decisive advantage in competence and time
  • you increase the efficiency of your products and ensure the high quality of your systems

Information Systems Services at Method Park

  • Establishment of an individual data analytics environment
  • Support on the journey from prototyping to the integration of Deep Learning-based algorithms
  • Connection of your systems to cloud services
  • Consulting on the topic of data analytics
  • Adaptation of your ALM tools
  • Creation of software engineering tools
  • Adaptation of your ALM tools
  • Creation of software engineering tools
  • Coaching and hands-on workshops on the topics of data analytics, machine learning and configuration/version control systems

Questions?

Any questions about our engineering service offers? Feel free to call us!

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The right composition for your project

Programming languages

  • Python
  • C#
  • Java
  • TypeScript

Frameworks

  • Pandas, NumPy
  • matplotlib, Seaborn, Bokeh, Plotly
  • Flask, Django
  • pytest
  • xUnit
  • .NET / .NET Core
  • Spring .Net
  • JavaFX
  • Node.js

Standards

  • ISO 13485
  • ISO 14971
  • ISO 27001 / TISAX

Databases

  • MongoDB
  • mySQL
  • PostgreSQL
  • Google BigQuery
  • Azure Cosmos DB

Processes

  • Scrum
  • Kanban
  • Scaled Agile (SAFe)
  • LeSS

Tools

  • Jupyter
  • Git
  • Jenkins
  • Gitlab / Github
  • Gerrit
  • AWS
  • Azure
  • Google Cloud
  • Docker
  • Kubernetes
  • Terraform, Pulumi
  • Hyper-V
  • Windows Virtual Desktop (WVD)
  • Elastic Search
  • Spark
  • Kafka
  • Jira
  • Confluence
  • IBM Jazz
  • Polarion
  • PTC Integrety

Numerous industries use big data to improve their products, services or added value. In these sectors, big data is particularly connected to the protection of collected data. The government determines how data can be recorded, processed and analyzed, and how companies must ensure the worthiness of protection of respondents. Since May 2018, the new General Data Protection Regulation has been binding; in Germany this regulation is implemented in the Federal Data Protection Act (BDSG-new). This article shows the differences between the old implementation of data protection in the Federal Data Protection Act and the new General Data Protection Regulation – particularly considering big data. In: MED engineering (Edition 4/2018)

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The Internet of Things enables the things in our business or day-to-day world for autonomous interactions with us and among each other. More focus has recently been put on the blockchain technology to achieve this goal. The most popular example is the cryptocurrency Bitcoin. The second generation of Bitcoins can execute so-called Smart Contracts. Although this technology sounds very promising, its current state is inestimable. This article explains the operating principle of blockchains and the access arrangements of both network types (permissionless ledgers, permissioned ledgers) and discusses their advantages and disadvantages. You can download the article here. In: Medizin+elektronik (edition 4/2017)

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