Anaconda provides access to the foundational open-source Python and R packages used in modern AI, data science, and machine learning. These enterprise-grade solutions enable corporate, research, and academic institutions around the world to harness open-source for competitive advantage and research. Anaconda also provides enterprise-grade security to open-source software through the Premium Repository.
$0
per month
Microsoft Power BI
Score 8.4 out of 10
N/A
Microsoft Power BI is a visualization and data discovery tool from Microsoft. It allows users to convert data into visuals and graphics, visually explore and analyze data, collaborate on interactive dashboards and reports, and scale across their organization with built-in governance and security.
On top of all the software that I have used, Anaconda is the best because in Anaconda we have built-in packages that provide no headache to install packages and we can design a separate environment for different projects. Anaconda has versions made for special use cases. …
Anaconda gives freedom to do anything with its packages, compared to other non-programming language-based softwares. It is almost possible to do anything with Anaconda. Anaconda brings ease of integrity because it is possible to integrate anything with a Python Py script, …
I prefer Anaconda due to the control I have at every level over the data and the visualizations. Power BI does a better job at guessing what graphics to use, but these usually aren't the most helpful. Anaconda and the slew of Python extensions that add incredible functionality, …
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.
In operations we use the tool for many different topics, from factory quality systems to high level reviews. We have created kind of an internal "App Store" based on Power BI where you have a lot of different dashboards for different solutions (cost, cash, health and safety, sales, factories, distribution centers...) and you as an user just need to get in that "App Store" and enter in whatever tool can be useful for you. It is open to all the operations employees and can use on demand. Also it has raised the imagination of our colleagues, as they are not only working by themselves creating new reports, but also raising fantastic ideas that can be extended for the usage of all the community.
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.
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.
The desktop app is great but needs a lot of performance improvements
No MacOS Version for the Desktop app, this is a big limitation for business since executives prefer Macs
Premium Cloud Version of Power BI is awfully expensive
On-Premise Version of the Power BI Reports Server is bundled only with SQL Server Enterprise License and cannot be purchased separately and requires Software Assurance Subscription
On-Premise Power BI Report Server doesn't support ADFS, AzureAD or any Claims-Based authentication platform, a sad disadvantage for enterprises
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.
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.
At this point, I think we all know who has taken the lead in the business intelligence and analytics market worldwide. With fresh new updates every other day on top of an already robustly built product with all features that one can dream of is a no brainer, I feel. Microsoft will invariably be synonymous with quality and professionalism.
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.
I can't really speak to the support overall, [but] I will say that in the almost three years I have used the system, I have only needed to contact their support team once. I think the team was helpful, but it did take some time for us to resolve the issues/ request that they had. I guess the good news is that the system is pretty stable, and I personally have rarely needed to contact their technical support team.
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!
[Microsoft] Power BI is practical and effective, like a hammer for a nail, it is easy to use and produces very quickly the results that in most cases are urgently required by clients (nice reports to share on the web). To start using [Microsoft] Power BI you need a business email address, with that you create an account in Power BI Service and in less than 1 hour you will have installed Power BI Desktop, a report will have been created and it will have been published on the web .
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.