Data Modeling

Definition of Data Modeling as it relates to Technology, Data Science, Data Analytics

Data modeling is a crucial component of data analytics, playing a pivotal role in structuring and organizing data to facilitate effective analysis. It involves creating conceptual, logical, and physical data models that accurately represent an organization's data, enabling efficient storage, retrieval, and management. By visually representing complex data structures, data modeling helps data analysts and scientists understand the relationships between different data elements, ensuring accurate interpretation and meaningful insights. Ultimately, data modeling is essential for optimizing data analytics processes, enhancing data quality, and facilitating effective decision-making in technology-driven organizations.

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  • [maas.com] Maas Database Applications GmbH – maas.com – Expert Data Modeling – Code Generation – Long Life Database Applications
  • [erwin.com] Data Intelligence Data Modeling Solutions | erwin
  • [EdgeAnalytics.us] Edge Analytics - Business Analytics & Modeling - Data & Analytics
  • [info.spatial.com] Spatial | 3D Modeling Solutions and Data Interoperability Tools
  • [Hydrologic.com] HydroLogic: hydroinformatics, data science, hydrological modelling
  • [Quanted.com] Quanted | Data Testing Solutions for Predictive Models
  • [docs.datasecurity.org] Data Security Maturity Model | Version 2.0
  • [odmx.org] ODMX – An information model and associated cyberinfrastructure for earth science data
  • [teslafi.com] TeslaFi.com Tesla Model S 3 X Y Data Logger
  • [marco-brambilla.com] Marco Brambilla – Data Science and Model-Driven Engineering.
  • [Prosopography.net] GitHub - IPIF/prosopogrAPhI: Tentative way towards a shared API for prosopographical data based on the factoid model (Bradley/Short 2005)
  • [adrm.com] ADRM Software | Industry Data Models
  • [DataScienceEthics.com] Data Science Ethics - Discussing Model Behavior
  • [DataSecurity.org] DSMM - Data Security Maturity Model
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