Spotfire Data Science

Formerly TIBCO Data Science with Team Studio and Statistica

I prefer Spotfire Data Science's approach. It is more natural and fits the way I think. I prefer to use Spotfire Data Science's VB for writing macros. It is real code, meaning that I do not need to trick the software to do what I need and there are no implied loops over solving simple problems. The graphs are publication quality and can be edited by hand or using a macro if I am building hundreds of them. Spotfire Data Science had a user-friendly approach to building lengthy data processing streams (in its workspaces). It is just so fast for analyzing a dataset that you have never seen before and efficient for ongoing work on the same data.

I think Spotfire Data Science does two things better than these other software tools. First, Spotfire Data Science is perfect for exploratory analyses. It's suggested models are great, and the visualizations provide a nice look at the data before any modeling is done. Second, Spotfire Data Science works quite well with other software tools. The software seems like it is built for the advanced modeler.

We used Excel sheets before Data Science came into the organization. The main difference is that I cannot dynamically change the data in Excel sheets, which eats away at least 2 to 3 workers' time. Now, with Data Science, dynamic reporting can be done pretty quickly, which saves a lot of work and increases our productivity.

Data Science is a more robust analytical platform. Alpine Data is similar but not as powerful. Spotfire is a great combination to visualize information before modeling.

Data Science seems to be built around the idea that analysts would prefer not to code when they don't have to. As such, Spotfire Data Science does a great job making available to average analysts techniques that are about as modern as they get. The way Data Science advances the analytical capability of analytics staff is second to none. On the downside, the software isn't cheap, and unless you have ongoing projects that require continued advanced analytics, it's not worth the effort. Additionally, it's not the fastest running tool, probably because of how much is stuffed into the point-and-click interface.

Microsoft Office is a classic. Older employees are much more familiar and comfortable with Office than new cloud-based applications. The drawback to Microsoft Office is it isn't cloud-based, and we end up with countless versions of documents and data all over the place. It becomes difficult to find the latest version of something or find the data organized in one easy to find document. Google Drive is a good bridge from Microsoft Office to the cloud-based (and free) programs. It is less powerful than Office, in most cases, but has been a good transition from hard-drive to cloud based data management. Spotfire was a great tool but very powerful with lots and lots of options for data management. It's a great tool, but easy to get lost with. Spotfire Data Science is a slightly more specified version with what is needed to data science management. It is great because it's cloud-based, can do much more than Google Drive or Microsoft Office, but is not quite as overwhelming as Spotfire. That's why we chose Data Science.

I personally like the collaborative and team-centered aspects of Spotfire Data Science better than most other programs. In this way I think it stands out among competitors with both its ease of use and fluid userface. Some of the other programs, such as MATLAB, seem to do a generally better job in the more simple, straightforward, or small projects

Used Mathematica (not in the list), which has greater overall functionality (outside of statistics), but Data Science is much easier to use, especially for analysts with limited experience.

SPSS, SAS

In the past, cost, ease of use, and versatility were what made me choose Data Science. However, the cost concern may be leading my company to pursue solutions like R programming instead.