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ANACONDA REVIEW
https://www.trustradius.com/data-scienceAnacondaUnspecified8.651101
Mauricio Quiroga-Pascal Ortega profile photo
March 09, 2018

ANACONDA REVIEW

Score 10 out of 101
Vetted Review
Verified User
Review Source

Overall Satisfaction with Anaconda

I use Anaconda myself, for Python, Spider and R. It’s used by the whole organization. In my area, we use Anaconda for importing libraries to train predictive algorithms that help our clients to estimate value sources.
  • Anaconda has iPython- Notebook that facilitates code writing in Python
  • It's very easy to install tour preferred the Python version
  • The risk of messing up the libraries is completely eliminated
  • It's hard to get security updates when you leave the system packages
  • There're some PyPI packages that Anaconda doesn't have. This obligates the user to package it by herself or using pip
  • Anaconda isn't as fast as PyPI publications
  • It has helped our organization to work collectively faster by using Anaconda's collaborative capabilities and adding other collaboration tools over.
  • By having an easy access and immediate use of libraries, developing times has decreased more than 20 %
  • There's an enormous data scientist shortage. Since Anaconda is very easy to use, we have to be able to convert several professionals into the data scientist. This is especially true for an economist, and this my case. I convert myself to Data Scientist thanks to my econometrics knowledge applied with Anaconda.
ANACONDA VS Alteryx Analytics: Even though I find Alteryx to be an excellent tool for managing extremely massive data, Anaconda is much better and easy for analytics.

Anaconda VS. MicroStrategy Analytics: Compared with Anaconda, MicroStrategy Analytics is very difficult to use and counter-intuitive

Anaconda VS. Power BI For Office 365: One of the main advantages of BI for Office 364 is its capacity to data connectivity. However, it's very hard to edit data connections, once BI for Office is deployed in other platforms
Anaconda is the best solution when you need to make more basic algorithm training. However, when the client necessity if completely new or there're poor libraries, anaconda is too basic.

When designing algorithms, I find ai-one to be very useful. Other tools that more suitable than Anaconda for more complex tasks are protege, biffblue and Nervana Neon