Data Science is World-Class, as Long as You Have Ongoing Projects that Need World-Class Analyses
February 04, 2019
Data Science is World-Class, as Long as You Have Ongoing Projects that Need World-Class Analyses
Score 10 out of 10
Vetted Review
Verified User
Overall Satisfaction with TIBCO Data Science (including Team Studio and Statistica)
Spotfire Data Science is used across the analytics department to develop data visualizations and perform advanced data analytics. The software offers well-structured ways to scrape data from the web, perform machine learning, implement neural networks, create publication-quality graphics, and other simpler analyses. The advantage of Data Science is that it walks analysts through the analysis process rather than needing to write custom code.
- Data Science does an awesome job with web scraping. It's the easiest tool out there to scrape web data.
- The point-and-click process for performing neural networks is awesome.
- The graphics produced by Data Science are as good or better than most other software tools.
- Because the software takes a point-and-click approach upfront, creating customization requires more effort than software that starts with coding. It's somewhat like Excel. Excel is great for the things it does, but when it requires VBA coding, another software tool is usually a better fit.
- If you're looking to create custom graphics outside of what is built in to Data Science, good luck, not easy.
- Data Science has a moderately sized user base, but nowhere near some of the free software tools. This can be challenging when looking for answers to questions.
- In terms of employee productivity, Data Science has had a positive impact. Analyses that used to take weeks to perform could be done within a day in Data Science. It's worth it as long as there are lots of advanced analytical needs.
- In some cases, Data Science was not worth the effort because some employees don't have the aptitude to take advantage of all the offerings of Data Science. These employees, for some reason, prefer Excel or R.
- Data Science had a positive return on investment in many cases when it not only made analyses simpler, but expanded the range of capability of analysts. Individuals learn new techniques from the software.
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.