Python IDLE vs. Sisense

Scenarios where python IDLE is well suited 1-Quick scripting and prototyping 2-Education and training 3-small projects utilities 4-exploring python libraries and modules Scenarios where python is less appropriate 1 large scale projects 2 complex debugging and profiling 3 multi language development 4 Advanced code analysis and inspection

I believe Sisense is perfectly suited for any organization of any size that have access to the proper resources, as the tool is very expensive. The data connectors come in all shapes and sizes out of the box, which allows a great deal of data control within the ElastiCubes. Additionally, while the platform only runs on Windows platforms, the web application can be accessed on any client: mobile, Apple, Windows, etc. This allows a much more flexible user experience, resulting in data and dashboards reaching further than any other tool.

Incentivized

• Firstly, I would say Python IDLE interface is user friendly.
• Easy to learn for the beginners.
• Syntax highlighting is nice features.
• Smart indent helps a lot.

Incentivized

• Customization - lots of supported and community plugins available. Users can also adjust the look and feel through JavaScript.
• Innovation - Sisense is continuing to push the envelope by developing new features through Sisense Labs.
• Customer support - the commitment to excellent customer service and ensuring organizations get the most out of their investment.

Incentivized

• Too simplistic
• Could not find source revision management integration support
• Only basic debugging is available
• Does not have data-science-specific notebooks (but can be installed separately)

Incentivized

• The usability of the application on mobile devices needs some improvement, especially navigation and filtering.
• Dashboards that are created by multiple users can be a bit of a hassle to share by Admins.
• If you need to embed dashboards into your website, you are require to buy a license separate from the user and platform license. This is a norm on most BI visualization tools, but Sisense can seem a bit on the high side, cost-wide.

I think the business and myself as a user has come to rely on SiSense as a dashboarding and quick ad-hoc reporting tool. I am hoping to integrate SiSense dashboards into more parts of the business in the future. We have reduced our report turn-around time for the most part from hours/days to minutes and in some cases almost the speed of thought. Reports are also easier on the eye and more easily distributed. I would also like to say that the support and professionalism from the SiSense team has been excellent.

The IDE Python IDLE is a good place to start as it helps you become familiar with the way Python works and understand its syntax.

This IDE allows you to configure the environment, font, size, colors, .....

It also looks like any simple text editor for any operating system, I work with Windows or Linux interchangeably, and you don't have to learn to use the IDE before programming.

Once the IDE is executed you can start programming directly in it.

Incentivized

New V5 is ground floor of an exciting collection of possibilities. Weekly Sisense developers come up with new functionality that they share with us in their forums. The move to HTML5 has been pleasing in that widgets auto size themselves into appropriate forms in the board but everyone of them can be popped out to full page size to be looked at in more detail

There are very few situations when there is unexpected downtime. Mostly during development, new dashboard implementation and during upgrades. other then that there were very few crashes.

SiSense is usually performing better then other solutions even if going for complex reports/dashboards(of course within reasonable frames). I haven't noticed any bad influence on other systems, usually if something happens it stays within SiSense.

Python IDLE support is what the community can give you. As it is free software, it does not have support provided by the manufacturer or by third-parties.

In any case, for most of the problems that normal users can find, the solution, or alternatives, can be found quickly online.

As this IDE is made in Python, the support is the same group of Python developers.

Incentivized

SiSense's support ninjas are very knowledgeable and are exceptionally responsive. So far, all of the issues we ran into were resolved within minimum time. My sense of dealing with the support staff at SiSense is that they are very focused on not just answering your immediate question, but also to delve into the cause of the matter.

Easy and free training that allowed us quickly understand basics in SiSense and start using them. More advanced features requires some browsing through SiSense forums, but there is always support to help, and SiSense support is one of the best whith which I worked so far.

Many examples, videos and scenarios which you try on your own right away. This combined with in-person training gives you enough to utilize most of SiSense's power.

Remember to migrate the plugins. The documentation however is pretty straight forward.

It's easy to set up and run quick analysis in Python IDLE on my local machine. The output is direct and easy to read. But sometimes I prefer Jupyter Notebook when the datasets are large, since it would take too long to run on my local machine. It is easier to run Jupyter Notebook on my cloud desktop

Incentivized

1) Easy to use, really, there is nothing too much to say. The set up is easy and not confusing. You can use it internally or externally.

2) Customer Service, having spoken to various product reps from similar industry. Sisense rep provides you with the best support to get started, and it is really appreciated.

Product is quite easily scalable. The whole installation can be easily moved to stronger machine if needed.

• In a short time, we were able to develop several ML models for various teams to make accurate decisions.
• Beginners can easily understand and adapt to GUI.
• We could automate several manual validation tasks and so could reduce human intervention.

Incentivized

• Report development time is reduced from 2~3 days to 2~3 hours.
• Report querying time is improved from 0.5~10 mins to 2~30 seconds.
• A 2-staff team delivers 10 times the BI output that we did on the old system.
• We were able to deliver BI and data analysis for all business functions instead of a very limited group of users