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
SAS Visual Analytics
Score 7.7 out of 10
Enterprise companies (1,001+ employees)
SAS Visual Analytics provides a complete platform for analytics visualization, enabling users to identify patterns and relationships in data that weren't initially evident. Interactive, self-service BI and reporting capabilities are combined with out-of-the-box advanced analytics so everyone can discover insights from any size and type of data, including text.
$0
Annual By Users: 5, 10, 20
Pricing
Anaconda
SAS Visual Analytics
Editions & Modules
Free Tier
$0
per month
Starter Tier
$9
per month
Business Tier
$50
per month per user
Enterprise Tier
60.00+
per month per user
SAS Visual Analytics for SAS Cloud
Annual By Users: 5, 10, 20
Offerings
Pricing Offerings
Anaconda
SAS Visual Analytics
Free Trial
No
Yes
Free/Freemium Version
Yes
No
Premium Consulting/Integration Services
Yes
Yes
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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SAS Visual Statistics and SAS Office Analytics are also available as add-ons.
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.
I was in a meeting with the client and there I have to show them some analytic data to them. But I was confused about how I will manage to show big data to clients with accuracy. But then the SAS Visual Analytics software helps me in presenting accurate data at the moment and it was very presentable and through that, I got the deal for that business.
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.
Provides the flexibility to the end user to slice and dice the data.
Anyone can make predictive models with the help of in-built algorithms without the need to write a single line of code or knowledge of what's under the hood of algorithms.
The feature to simply ask a question related to data and getting a response in form of text, chart or graph is amazing.
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.
SAS is relatively expensive when compared to other BI tools and requires a large amount of upfront fee which becomes an issue for smaller organizations.
UI for the dashboards looks a little date in comparison to competitors like Tableau and Microstrategy.
Integration with other open source software like Python needs to be built in.
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.
SAS really is the cutting edge in Business Intelligence. That is all they do! They are constantly coming out with new products, product upgrades, and their tech support is second to none. In addition, their support of Education has made our ability to acquire their product possible.
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.
SAS BI is good for creating reports and dashboards and then sharing it with the users. It also has ability to manage access to the reports and dashboards but somehow with most of the world moving to open source languages R, Python and Julia, SAS BI feels to be archaic in terms of feature set and integrations it allow[s]. Also, comparing it with other Business Intelligence tools like Tableau and Microsoft BI, the functionality of SAS BI is very limited and doesn't justify the pricing.
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.
When you call tech support, you are immediately routed to a person who can answer your question. Often they can answer on the spot. However, if they cannot, you are given a track number and then followed up with. There have been times when I have had multiple track numbers open and they will actually TRACK YOU DOWN to ensure that your problem has been resolved. Issues do not fall into black holes with SAS. They are also willing to do a WebEx with you to diagnose the problem by seeing your environment, which is always helpful.
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!
I have used Crystal Reports, Jaspersoft and SQL Server Reporting Services (SSRS). I would recommended Business Intelligence over SSRS and Crystal Reports. SSRS is very SQL-centric and Crystal Reports is more of an end-user tool. I would recommend Jaspersoft over Business Intelligence for developing a seamless web-based reporting interface but I highly recommend Business Intelligence for end-user ad-hoc reporting.
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.
