Anaconda vs. Plotly Dash

As a Data Analyst, it is my job to analyze large datasets using complex mathematical models. Anaconda provides a one-stop destination with tools like PyCharm, Jupyter, Spyder, and RStudio. One case where it is well suited is for someone who has just started his/her career in this field. The ability to install Anaconda requires zero to little skills and its UI is a lot easier for a beginner to try. On the other hand, for a professional, its ability to handle large data sets could be improved. From my experience, it has happened a lot that the system would crash with big files.

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Applicable for data visualization across disciplines. I have used it for data from buildings, building occupancy, public health, and statistics. It is a useful tool to use for big data. It has nice templates and a number of interesting visualization types. If you are familiar with R and python it is easy to use.

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• It provides easy access to software like Jupyter, Spyder, R and QT Console etc.
• Easy installation of Anaconda even without much technical knowledge.
• Easy to navigate through files in Jupyter and also to install new libraries.
• R Studio in Anaconda is easy to use for complex machine learning algorithms.

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• Powerful visualization options.
• Ability to create in-browser interactive visualization apps.
• Ability to create hosted apps.
• Allows you to develop web-based reporting applications without requiring web application development expertise.

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• Although I have generally had positive experiences with Anaconda, I have had trouble installing specific python libraries. I tried to remedy the solution by updating other packages, but in the end, things got really messed up, and I ended up having to uninstall and reinstall a total of about 4 times over the past 2 years.
• If you have the free version of Anaconda, there is not much support. Googling questions and error messages are helpful, but there were times when I wished I would have been able to ask technical support to help me troubleshoot issues.
• There were a few times when I tried to install tensorflow and tensorboard via Anaconda on a PC, but I could not get them to install properly. Anaconda allows you to create 'environments' , which allow you to install specific versions of python and associated libraries. You can keep your environments separate so they do not conflict with one another. Anyway, I ended up having to create several 'conda envrionments' just so I could use tensforflow/tensorboard and a few other utilities to avoid errors. This was somewhat annoying, because every time I wanted to run a specific model, I'd have to open up the specific conda environment with the appropriate python libraries.

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• Would be good if Dashboard Engine was included in the Enterprise VPC plan
• Would love to see ready made fintech apps

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It's really good at data processing, but needs to grow more in publishing in a way that a non-programmer can interact with. It also introduces confusion for programmers that are familiar with normal Python processes which are slightly different in Anaconda such as virtualenvs.

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The interface is an easy to use command-line interface, or a GUI for launching and/or discovering different parts of the system.

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Anaconda provides fast support, and a large number of users moderate its online community. This enables any questions you may have to be answered in a timely fashion, regardless of the topic. The fact that it is based in a Python environment only adds to the size of the online community.

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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

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• Positive: Lower maintenance cost compared to other tools on the market
• Positive: Ease in hiring professionals already accustomed to the tool in the job market
• Positive: Projects are portable, allowing you to share projects with others and execute projects on different platforms, reducing deployment costs

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• A no-cost option as it is open sourced.

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