Anaconda

Anaconda

Top Rated
About TrustRadius Scoring
Score 8.7 out of 100
Top Rated
Anaconda

Overview

Recent Reviews

Anaconda Review

8 out of 10
June 28, 2021
I am a machine learning engineer and certified data scientist who is solving some real-world problems and used to teach students. I …
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Hemant's review of Anaconda

7 out of 10
May 21, 2021
Anaconda is currently used as the complete python environment setup tool. It has been easy for us to automate the process of setting up …
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My Anaconda Review

8 out of 10
May 21, 2021
Anaconda is not just a tool it is a complete package to build and deployment of the project related go machine learning , neural networks, …
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Awards

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Popular Features

View all 16 features

Data Transformations (25)

8.8
88%

Extend Existing Data Sources (23)

8.7
87%

Interactive Data Analysis (23)

8.6
86%

Visualization (24)

8.6
86%

Reviewer Pros & Cons

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Video Reviews

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Pricing

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Commercial Edition

$14.95

Cloud
per month

Team Edition

10,000

Cloud

Enterprise Edition

Contact for quote

Cloud

Entry-level set up fee?

  • No setup fee

Offerings

  • Free Trial
  • Free/Freemium Version
  • Premium Consulting / Integration Services

Features Scorecard

Platform Connectivity

8.4
84%

Data Exploration

8.6
86%

Data Preparation

8.5
85%

Platform Data Modeling

8.6
86%

Model Deployment

8.2
82%

Product Details

What is Anaconda?

Anaconda is an open source Python distribution / data discovery & analytics platform.

Anaconda Video

Anaconda Introduction

Anaconda Technical Details

Deployment TypesSaaS
Operating SystemsUnspecified
Mobile ApplicationNo

Comparisons

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Reviews and Ratings

 (113)

Ratings

Reviews

(1-25 of 37)
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Zayed Rais | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Review Source
Anaconda is the best tool for the data scientist to [develop] the machine learning project [under] a single umbrella. It is used [throughout] the whole organization. We are using the Anaconda for Python [and] R to do the data science activities end-end process, i.e. importing the statistical/ML/Visualization libraries to train and visualize the data/reports.
Score 7 out of 10
Vetted Review
Verified User
Review Source
Anaconda open-source distribution is a flexible platform enabling users to work with several popular data analytics languages such as R and Python.

It is being used by Engineering and Geoscience teams to prototype custom algorithms for use in solving use cases in the oil and gas industry, including subsurface, operations and other relevant functional area such as health, safety and environment.
Jay Thakkar | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Review Source
Anaconda is mainly used for Python programming like data science and computer vision script.
Advance mathematics operation is easily done by Anaconda.
I mostly used Jupyter Notebook and Spyder.
It makes it easy to script in python through the user interface of Anaconda software.
Accessing libraries of python through Anaconda is easy and efficient.
June 28, 2021

Anaconda Review

Dilip Jain | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Review Source
I am a machine learning engineer and certified data scientist who is solving some real-world problems and used to teach students. I generally used to work on the project that is beneficial for me as well as the society to make life easier. I used to create machine learning models and host them on the cloud. I used Anaconda as my primary software to work on my projects. Best for setting your Python environment. Anaconda is the best data science version control tool in the present time. This is the best solution that is packed with lots of ideas and good features. With anaconda, you can easily create, remove, and switch environments to run.
Score 9 out of 10
Vetted Review
Verified User
Review Source
My previous organization used Anaconda, Jupyter Notebook specifically to run sales forecasting codes in Python. At the time, it was specifically used by the E-Commerce and Buying team to make buying decisions. The ease of using Anaconda Navigator was a very big plus point for my organization as they could save a ton of time and money that was needed behind the training.
Score 10 out of 10
Vetted Review
Verified User
Review Source
The teams which are working on analytics-based projects are using Anaconda/Anaconda Navigator for various other tools. Like building small applications using python on Spyder is used in it. Also for reporting and visualization R and Orange has used it.

Used department and Teams wise as per the requirement from the stakeholders. Not every team is using this navigator.
Score 10 out of 10
Vetted Review
Verified User
Review Source
Anaconda is being used by the Business Intelligence and Data Science department at my organization. It is used widely for analysis, forecasting and answering questions. For example, the commercial department wanted to know which of their three products was most affected by COVID-19. So using Anaconda Jupyter Notebook and data from surveys conducted with customers we could come to a conclusion. It was easy to represent the findings in visual forms.
Score 7 out of 10
Vetted Review
Verified User
Review Source
Anaconda is currently used as the complete python environment setup tool. It has been easy for us to automate the process of setting up the coding environment for all of our employees. We have created separate environments for separate purposes. Anaconda has been very useful. Not only [do] we have every requirement at one place but we can also manage it more efficiently and debug problems more easily
May 21, 2021

My Anaconda Review

Score 8 out of 10
Vetted Review
Verified User
Review Source
Anaconda is not just a tool it is a complete package to build and deployment of the project related go machine learning , neural networks, artificial intelligence. It is loaded with the pre built library. Anaconda provide the facilities for the data visualization. Starting with the normal python script you can even create the whole data science project along with the deployment. In my second year of college I use the Anaconda [to] build my machine learning project which is based on predicting the food item in the given plate. For that i done all the computing using this software only.
Currently we are working on predicting the client requirements in our company. So we are using there preference and choice or decision made by them and according to that we will provide the recommendation.
Fernanda Ministerio | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source
The company has several departments and distributed units that are adopting the use of data science to improve institutional performance. Anaconda has been used as a tool to support professionals who improve data and their results for the management of the organization. We still have a lot to evolve in data management, integration, standardization, and data improvement; but the continued use of Anaconda will allow us to identify our bottlenecks and make better decisions.
Score 7 out of 10
Vetted Review
Verified User
Review Source
Anaconda is a great package manager for large-scale projects with multiple dependencies and support for multiple versions of python. It offers us out-of-the-box capabilities for major common data science use cases and projects. Really robust in terms of switching execution environment and offers granular control over the Conda virtual environments. It is used across our organization as it has really great community support and they offer solutions in case we are stuck as well.
Score 9 out of 10
Vetted Review
Verified User
Review Source
Our team is using Anaconda as a python distributions tool for running python code. It contains and supports the maximum number of python libraries and packages. It has helped us to set up a complete data analysis environment with the help of Jupyter Notebook.
Score 9 out of 10
Vetted Review
Verified User
Review Source
Anaconda is a standard installation for our python coders. Our python coders stretch across multiple departments so it should be considered being used by the whole organization. Anaconda makes it easy for us to standardize getting a base working environment ready for everyone. From there it makes is easy for users to install required packages.
April 16, 2021

Review for Anaconda

Tigran Petrosyan | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source
Anaconda is mainly used only by some of the departments in our bank. Specifically in our department it is mainly used as a environment for coding in python although some of my colleagues use it as a environment for coding in R. As risk managers we usually do some complex tasks using python (to predict exchange rate fluctuations and evaluate market and credit risks).
Score 9 out of 10
Vetted Review
Verified User
Review Source
Anaconda Navigator is used across a few departments as a way to share code that is used to analyze data from our products. The data is stored in the cloud. Some engineers write the code to analyze and print results for manufacturing tests. The manufacturing team can then easily run the code to receive the results of the tests.
Juande Santander-Vela | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source
The usage of Anaconda is not yet standard through the organization, but many people at my organization use it as the best way to create a standardized Python environment. In particular, the Miniconda distribution is preferred for deployment of Python-based containers, as it allows for a better, finer-grained installation in containers. For desktop users, the full Anaconda distribution is used, as it comes with several packages that are used throughout the organization: Astropy, NumPy, Matplotlib, Pandas, and others.
Ryan McGarry | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source
We use Anaconda to support software development objectives for our staff. It helps us reduce "time waste" by quickly onboarding employees and setting up the majority of their development environments, so they have all of their necessary tools.
Xiaotong Song | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source
Anaconda is being used in the entire organization of my company. It ensures that data science teams across the whole organization manage our python environment and make sure the repeatability of the packages that we built internally as well as the notebooks and projects created by different teams.
Score 10 out of 10
Vetted Review
Verified User
Review Source
Anaconda is widely used in my organization to set up the python environment and perform version control. By setting up the environment yaml file, you can ensure the other users can run the analysis based on the same environment. Also, Anaconda provides other tools such as RStudio/spyder via the navigator.
Score 7 out of 10
Vetted Review
Verified User
Review Source
The data science and operation research team in our company majorly uses Python as the programming language. So Anaconda was chosen to provide one research platform, allowing the data scientists to work on one unified environment, across different OS, using the same language while being able to share the work progress as well as results and promote the team efforts.
Score 10 out of 10
Vetted Review
Verified User
Review Source
We use the Anaconda package for physics and engineering research. We get large data in accelerator physics experiments. We use Anaconda for many purpose, but especially for its Python libraries. We have mainly used this platform for data analysis and making a nice plot. Many faculty, staff and students are using it in their research.
Score 10 out of 10
Vetted Review
Verified User
Review Source
We're using it in our department for data-related business needs, data retrieval, data manipulation, data preprocessing, visualization, forecasting, and prediction. So whether the business problem is a simple data analytics problem or complex modeling, Anaconda is used in our department. We use Anaconda for its Python libraries that come as a package, which is great. Not to mention that it eases the pain of updating all packages that would otherwise be carried out one by one for each. We use Panda's library within Anaconda to read, manipulate, preprocess and write the data. We use Numpy for mathematical functions. We use Matplotlib and Seaborn for data analysis and visualization. Finally and most importantly, we use Sci-kit Learn to create predictive models because it contains almost all the algorithms we need. Sadly, it does not contain XGBoost, CatBoost or LBGM however it is easy to install those with Anaconda because that's what Anaconda is for - helping managing all these packages, whether it is installation or simply updating.