Consultant - Data Analytics and Reporting at a tech vendor with 51-200 employees
Real User
Apr 3, 2024
The tool's most valuable feature is its cloud-based nature, allowing accessibility from anywhere. Additionally, using Jupyter Notebook makes it easy to handle bugs and errors.
Global Data Architecture and Data Science Director at FH
Real User
ModeratorTop 5
May 14, 2021
With Anaconda Navigator, we have been able to use multiple IDEs such as JupyterLab, Jupyter Notebook, Spyder, Visual Studio Code, and RStudio in one place. The platform-agnostic package manager, "Conda", makes life easy when it comes to managing and installing packages.
Analytics Analyst at a tech services company with 10,001+ employees
Real User
Aug 13, 2020
It's interesting. It's user friendly. That's what makes it outstanding among the others.
It has a collection of R, Python, and others. Their platform strategy has a collection of many other visualization tools, apart from Spyder and RStudio, which is really helpful for data science. For any data science professional, Anaconda is really handy. It has almost all the tools for data science.
Anaconda Platform provides enterprise teams with a governed foundation for building, securing, and running Python, data science, and AI workloads, from local development through production.
Anaconda Platform gives data science, machine learning, and AI teams a single system for sourcing, securing, building, and deploying open source. It extends the Anaconda tooling practitioners already use, including Anaconda Distribution, Navigator, and the conda package manager, into a centrally managed...
The tool's most valuable feature is its cloud-based nature, allowing accessibility from anywhere. Additionally, using Jupyter Notebook makes it easy to handle bugs and errors.
I can use Anaconda for non-heavy tasks.
With Anaconda Navigator, we have been able to use multiple IDEs such as JupyterLab, Jupyter Notebook, Spyder, Visual Studio Code, and RStudio in one place. The platform-agnostic package manager, "Conda", makes life easy when it comes to managing and installing packages.
The documentation is excellent and the solution has a very large and active community that supports it.
It's interesting. It's user friendly. That's what makes it outstanding among the others.
It has a collection of R, Python, and others. Their platform strategy has a collection of many other visualization tools, apart from Spyder and RStudio, which is really helpful for data science. For any data science professional, Anaconda is really handy. It has almost all the tools for data science.
The product is responsive, sleek and has a beautiful interface that is pleasant to use. It helps users to easily share code.
The virtual environment is very good.
The most valuable feature is the Jupyter notebook that allows us to write the Python code, compile it on the fly, and then look at the results.
The solution is stable.
The most valuable feature is the set of libraries that are used to support the functionality that we require.
The most advantageous feature is the logic building.
The notebook feature is an improvement over RStudio.
The best part of Anaconda is the media distribution that comes as part of it. It gets us started very quickly.
It helped us find find the optimal area for where our warehouse should be located.