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
Sisense for Cloud Data Teams
Score 6.5 out of 10
N/A
Sisense for Cloud Data Teams (formerly Periscope Data) is a data visualization tool that allows users to connect to their SQL databases to create sharable, interactive dashboards. In addition to SQL, its analytics integrate with R and Python, allowing users to prep datasets, perform analysis, and create their own visualizations. Sisense acquired Periscope Data in mid-2019.
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.
Sisense for Cloud Data Teams is suited so well for our project that works with lots of data and needs some ways to share data internally or externally with our clients. It's very easy to pull out the data from the sense in best and in a suitable format and moreover a huge number of options are available there to represent the data. All features of this Sisense for cloud data teams software can be taken advantage of if you have a team who are well versed in data analytics, data management, and programming.
Rapid deployment of polished T-SQL-based data visualization charts and dashboards. Periscope supports a variety of database technologies, and allows users to write custom queries to display data.
Included caching to reduce server load.
Outstanding customer service/support, with expert advice as needed.
Constant updates and new features.
Built-in SQL formatters take the pain out of manipulating date/time objects.
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.
Include more appropriate updates in their monthly newsletter as opposed to the general overview that doesn't always have the most pertinent information at the forefront.
There are bugs at times when certain dashboards are down, though not in an overwhelming way.
If you do not tag something it shows up in multiple views and may be accessible to people that it should not be, though that is a user error it may make sense to prompt for a tag and security setting.
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.
My company has had Periscope for various use cases in the past and I think that this program opens up complex data reports to non-technical people in a really accessible way (even though the learning curve is a big one). We are now integrating Sisense for Cloud Data Teams at a larger level both for internal data exploration and for customer facing dashboards and reports.
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.
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
Google Analytics works well but it does not have all of the bells and whistles that Periscope Data offers. Google Analytics is best used in a Google environment but if you are using other tools and programs outside of the Google universe, then Periscope Data is a much better option.
