Anaconda vs. botkeeper vs. CCH Axcess

I have asked all my juniors to work with Anaconda and Pycharm only, as this is the best combination for now. Coming to use cases: 1. When you have multiple applications using multiple Python variants, it is a really good tool instead of Venv (I never like it). 2. If you have to work on multiple tools and you are someone who needs to work on data analytics, development, and machine learning, this is good. 3. If you have to work with both R and Python, then also this is a good tool, and it provides support for both.

Incentivized

Well, Suited Scenarios are: Automating the data entry, analysis, bookkeeping, managing finances fairly on this basis, and pulling out burndown charts, reports, and other analytical chapters. hence it helps in understanding the business, cash flows, or issues related to that which surely end up with the ideas of revenue growth directly and indirectly as well. And the most important thing in all this is done by AI-powered tools so management of resources overhead is no more. Scenarios where it is less appropriate: When it comes to a strong comprehensive accounting then the bookkeeper fails there and we need to integrate with third-party service providers to achieve the goal. So this is the worst scenario. And for detailed resources, one needs a vast knowledge base, and that's not the case with the Botkeeper as its knowledge base appears to be limited to basic.

Incentivized

This application is best suited for enterprise use cases. It interfaces with almost every other major platform at the enterprise level and is scalable to the nth degree. But that comes at a high price tag, given that it integrates with everything and is used relatively ubiquitously. Any recommendations that I would give on the platform would be based on enterprise applicability.

Incentivized

• Anaconda is a one-stop destination for important data science and programming tools such as Jupyter, Spider, R etc.
• Anaconda command prompt gave flexibility to use and install multiple libraries in Python easily.
• Jupyter Notebook, a famous Anaconda product is still one of the best and easy to use product for students like me out there who want to practice coding without spending too much money.

Incentivized

• They have a clean and easy portal that I can log into and link all accounts so they have access to what they need
• They are so good at what they do that I only need to respond to 1 or 2 emails a month for uncategorized transactions or clarifications
• They process all of our AR, AP, year end reports, sales tax, and bookkeeping. And it's all very accurate and on time.

Incentivized

• CCH Document - It's cloud based. The program is user-friendly and easily customizable.
• CCH Tax - Relatively easy system navigation. It satisfies all our tax return filing needs.

Incentivized

• It can have a cloud interface to store the work.
• Compatible for large size files.
• I used R Studio for building Machine Learning models, Many times when I tried to run the entire code together the software would crash. It would lead to loss of data and changes I made.

Incentivized

• their current interface
• the scoping tool (makes sense once you're using botkeeper)

Incentivized

• Customer support does not know their own product!
• Rep for the company does not know their own product!
• Hidden add-ons that they deceive prospect into believe is apart of the system.

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.

Incentivized

I am giving this rating because I have been using this tool since 2017, and I was in college at that time. Initially, I hesitated to use it as I was not very aware of the workings of Python and how difficult it is to manage its dependency from project to project. Anaconda really helped me with that. The first machine-learning model that I deployed on the Live server was with Anaconda only. It was so managed that I only installed libraries from the requirement.txt file, and it started working. There was no need to manually install cuda or tensor flow as it was a very difficult job at that time. Graphical data modeling also provides tools for it, and they can be easily saved to the system and used anywhere.

Incentivized

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.

Incentivized

I have experience using RStudio oustide of Anaconda. RStudio can be installed via anaconda, but I like to use RStudio separate from Anaconda when I am worin in R. I tend to use Anaconda for python and RStudio for working in R. Although installing libraries and packages can sometimes be tricky with both RStudio and Anaconda, I like installing R packages via RStudio. However, for anything python-related, Anaconda is my go to!

Incentivized

Botkeeper is quite new to accounting solutions. The tech base is quite new and cutting edge. Service support is quite fast and good. Integration support is open to another third party to enhance in all possible ways. Eliminates overhead of hiring permanent resident accountants. Great user experience and well-optimized tools.

Incentivized

CCH Axcess was very comparable to Thomson Reuters. They are both large companies in their fields and have similar resources. We ultimately went with Thomson Reuters because we bundled with their other softwares for a better price and it makes sense to be with one company to deal with one customer support line.

Incentivized

• 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.

Incentivized