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Analytics & Visualization Software

Beyond programming languages, many researchers use dedicated software for statistical analysis, data visualization, and business intelligence. These tools often provide graphical interfaces and are well-suited for specific workflows or disciplines.

Statistical & Scientific Software

SoftwareDescriptionBest forLicense
MATLABHigh-level language for numerical computation and engineering simulationsEngineering, signal processing, control systemsProprietary (TUM License)
SPSSPowerful platform for advanced statistical analysisSocial sciences, survey analysis, psychologyProprietary
MinitabUser-friendly tool for quality improvement and teaching statistical conceptsQuality control, Six Sigma, educationProprietary
StataStatistical software for data management and analysisEconomics, epidemiology, political scienceProprietary
JMPVisual statistical discovery softwareExperimental design, exploratory data analysisProprietary

Data Visualization & Business Intelligence

These tools focus on creating interactive dashboards and reports from data, often with drag-and-drop interfaces.

SoftwareDescriptionBest forLicense
Microsoft Power BITool for building interactive reports with live data refreshBusiness reporting, dashboards, M365 integrationProprietary (TUM M365)
TableauIntuitive 'drag-and-drop' interface for exploring large datasetsData exploration, storytelling with dataProprietary
Looker Studio (formerly Google Data Studio)Free web-based dashboarding toolQuick reports, Google ecosystem integrationFree
Apache SupersetOpen-source business intelligence web applicationOrganizations preferring open-source solutionsOpen Source

Spreadsheets

  • Excel: Common for quick data entry and basic analysis, but generally not recommended for complex, reproducible data pipelines due to formatting issues and lack of version control.
  • Google Sheets: Web-based alternative with real-time collaboration, but shares similar limitations for research reproducibility.
When to Use What
  • Quick exploration or one-off analysis: Spreadsheets, Power BI, Tableau
  • Reproducible research pipelines: R or Python with version-controlled scripts
  • Discipline-specific workflows: MATLAB (engineering), SPSS (social sciences), specialized tools