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
Dundas BI
Score 8.9 out of 10
N/A
Dundas BI is a business intelligence and data visualization software that includes customizable dashboards, reporting, and visual data analytics. Dundas BI can be integrated into users’ existing business applications and its visualization and reporting tools can be customized to their needs.
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.
For all the scenarios I have so far worked on or I am currently working on, Dundas BI has proved to be more than adequate and apt to handle all of those. It is a very easy-to-use tool with quick shortcuts enabling you to prepare ad-hoc reports or dashboards in a matter of minutes.
Project organization from Development to Production, you get a production and development license but I think the best way to do it is with DEV and Prod project in the Production box. Use the development box for testing updates and really crazy things. With the Dev and Prod projects on the same box, you just publish from Dev to Prod and you are done. Users only have access to the Prod projects so no one can mess up what you are working on.
Security - If you have a hierarchy (subsidiaries, divisions, department, teams) and you want each group to see only their data, then Security hierarchies are for you!
Dependent filters! What's this you ask? Here is an example of how it can be used, in your company you have departments and who works for what department is in your database. You make a dashboard that has a department filter (only show these departments), a managers filter, and employee filter. Not every manager or employee is in multiple departments usually only one. With dependent filters you can say that the manager and employee filter are dependent on what is selected in the departments filter so when you go to filter them they only show the managers or employees that are part of that department, and you can even it do so employees are not only dependent on department but on manager as well. Then it gets even better as it can be done in reverse as well so when you select a manager then go to the department it only shows the departments he works for (there are better situations where this is more useful).
It is scriptable! From calculate columns, null replacements, button actions, load actions, hover over events there a way to do what you want.
They are constantly improving and listens to your suggestions.
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.
Not too many cons for how we use the application. It really is easy and powerful. Very powerful.
Licensing is one thing that could be looked into. It is simple, but a little confusing. For example, if I get a license today, but a new release comes out tomorrow, it seems that the license doesn't work with the new release. Maybe that is by design, but it would be nice to clearly understand.
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.
We are still in the implementation phase, but so far we are finding it to be easy to use and learn. The eLearning courses that they have made available for free, as well as User Forums and other training videos have made even difficult concepts easier to understand.
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.
We have bi-weekly calls with our Success Manager, as well as access to support as needed. Any question that I have had, multiple people have been willing and able to jump on a call to talk me through it, or send an email with the solution
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
Per dollar spent, it offers the widest range of features of the tools that we evaluated. It offers lots of options for how to configure your environment, though they are not always intuitive to figure out. Having an ETL layer was a must have for us, as well as the ability to host to secure HIPAA compliance. It is not a replacement for ad hoc reporting, but does a great job of creating parameterized reports and dashboards that look great.
