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erwin Data Modeler

Understand complex data sources and design and deploy new ones
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What is erwin Data Modeler?

It is data modeling tool used to find, visualize, design, deploy and standardize high-quality enterprise data assets. Discover and document any data from anywhere for consistency, clarity and artifact reuse across large-scale data integration, master data management, metadata management, Big Data, business intelligence and analytics initiatives – all while supporting data governance and intelligence efforts.
erwin Data Modeler is a tool in the Data Science Tools category of a tech stack.

erwin Data Modeler's Features

  • Visualization of Any Data From Anywhere
  • Automated Data Model & Database Schema Generation
  • Centralized Model Development & Management
  • Data Literacy, Collaboration & Accountability
  • Agile Application Development
  • Increased Data Quality

erwin Data Modeler Alternatives & Comparisons

What are some alternatives to erwin Data Modeler?
Pandas
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more.
NumPy
Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.
Anaconda
A free and open-source distribution of the Python and R programming languages for scientific computing, that aims to simplify package management and deployment. Package versions are managed by the package management system conda.
SciPy
Python-based ecosystem of open-source software for mathematics, science, and engineering. It contains modules for optimization, linear algebra, integration, interpolation, special functions, FFT, signal and image processing, ODE solvers and other tasks common in science and engineering.
PySpark
It is the collaboration of Apache Spark and Python. it is a Python API for Spark that lets you harness the simplicity of Python and the power of Apache Spark in order to tame Big Data.
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