Tableau vs SPSS Statistics

Tableau Desktop is a BI solution for data visualization, dashboarding and location analysis. In online reviews, users said they found its drag-and-drop charting a boon for creating charts and maps. Regarding customization, many users praised the platform for its various labeling and design options.I recently tried the Tableau Desktop 2024.1.3 version. The trial is only for 14 days and is enough for a sneak peek into Tableau’s dashboarding and data storytelling capabilities. For more straightforward use cases, Tableau is incredibly user-friendly and fast. Creating a new sheet gives you a canvas to create a visualization. Once you have the required sheets, combining them into a dashboard view is straightforward — select and add.My dataset included healthcare data, including details of patients, their hospital visits and insurance payer details. One use case was to find the total claim settlement amount. I dragged the Total Claims Cost and Payer fields to the column and row shelves, and Tableau gave me a bar graph. The toolbar had single-click options for sorting data from increasing to decreasing values or the other way around.To view the number of encounters by payer, I dragged the Payer field to the row shelf and used the SUM(ROW_COUNT()) function on the column shelf. The chart popped up with more visualization and layout options.I wanted an interactive filter to view the average claim cost by birthdate. I dragged the Birthdate field to the Filters shelf and right-clicked on it to set the end date as October 22, 1961. Selecting Show Filter added a slider conveniently to the right of my visualization. I could see the data for people born before October 22, 1961, and if required, I could change the end date.Another use case would be viewing the data by the type of hospital visits — how many people were inpatients, outpatients or those who needed emergency care. I dragged and dropped the Total Claims Cost and Payer fields into columns and rows, respectively. Similarly, I dropped Encounterclass into the Filters shelf and clicked on Show Filter to enable a checkbox on the screen. It had all the categories of visits, giving users the option to select the desired views.One-fourth of the users discussing adoption said there was a steep learning curve. Tableau relies on Python and R scripts for statistics in its visualizations. It's where the named licenses can prove to be a blessing, as you can opt to train upcoming Creators and Explorers. We recommend factoring in training if you want to hit the ground running.Some reviewers felt discounted packages for business editions should be available, similar to the free student licenses. At $70 per user, the Creator license can seem costly when compared to Power BI ($9.99 per user) and Qlik Sense ($30 per user).Here's the good news, though. Its built-in user management acts as a permissions layer for your organization - users can only access the relevant content. Plus, an organization will have very few Creators and a greater number of Viewers and Explorers, and the license fee reduces from Creator to Explorer to Viewer.We recommend opting for a wise license combination to get the most out of the product.On the upside, the vendor constantly releases new features, the latest one being Einstein CoPilot in beta.Overall, Tableau is a competitive BI solution, but if the pricing seems inflexible, quite a few other solutions offer live insights and advanced analytics out of the box.

SPSS Statistics is a point-and-click data analysis software that allows non-technical users to leverage advanced statistical analysis. Users praised its user-friendly, visually appealing interface. Many reviews also appreciated how easy it is to use and proof syntax, along with the extensive help documentation available for better understanding. Despite its ease of use, a majority found that using advanced tools involved a steep learning curve. Additionally, its cost runs on the high side and processing large amounts of information slows down its performance, as observed by most reviewers. It’s a good fit for students, data scientists and companies that want to analyze data sets but don’t have the technical resources and expertise to use a more advanced tool.