Tableau Desktop: Making an Impact in the World of Drug Safety
Updated June 21, 2017

Tableau Desktop: Making an Impact in the World of Drug Safety

Anonymous | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User

Software Version


Overall Satisfaction with Tableau Desktop

Tableau is being used within the Commercial side of business and within the R&D side within the Drug Safety department of which I am a part of and which will be the focus of my review. It is being used primarily in support of operational analytics and workflow management within the Drug Safety organization, as well as for risk management within the Pharmacovigilance and Risk Management organization. Many if not all drug safety databases capture data well, and output data decently...but only for pre-defined outputs (native to the drug safety database out-of-the-box functionality), however getting data out of the database in flexible, easy to understand graphs and tabulations is much more difficult. That is where Tableau shines...first of all it allows the user to easily access data stored in an Oracle-based database and many other data formats, and it makes this easy connection without needing any interim transformation, catalog or universe to be created. This is a huge time savings, allowing the user to focus on getting information out of the data instead of just getting to the data. So the big business problem it solves is that it allows easy access to data...and allows the user to quickly turn the data into actionable information. To give our users easy access we create dashboards with visualization and filtering capabilities, and manage the users in Tableau Server in user groups with pre-defined access rights, so it is very easy to add new users and enable them to derive information from data.
  • Allows the user to easily access data stored in an Oracle-based database and many other data formats, and it makes this easy connection without needing any interim transformation, catalog or universe to be created. This is a definite strength as other analytical applications require data to be stored in or accessed via an interim format.
  • The drag and drop nature of the user interface and the fact that it begins to understand your data is a great feature allowing very rapid creation of analytical visualizations and tabulations.
  • The ability to allow the desktop user to quickly and easily push out a series of visualization dashboards to Tableau Server is a great part of its functionality, and allows the visualizations to be more readily used across and organization.
  • The biggest area needing improvement is in the area of placement of objects in a dashboard during its design. The placement is sometimes quirky and does not necessarily translate to an optimal placement on the dashboard which has been pushed to Tableau server.
  • It would be nice to have the capability to point at a pre-defined style template which would help in creating consistency in terms of default placement of objects and overall look & feel.
  • Within the pharmaceutical industry, the ability to seamlessly read in a SAS dataset would be very useful, as currently this involves at least one interim step.
Against the usual incumbents within the pharmaceutical industry, Tableau has much better and faster access to database data especially stored in the Oracle database, without needing any interim transformations or data universe needing to be created. Also it has comparatively good access to other data sources such as spreadsheets, which can be problematic for other analytic tools.
Tableau has delivered well for our organization, there is a lot of interest in it within the pharmaceutical industry and it has only scratched the surface. Tableau has a very good ROI and it takes very few people to support, yet provides a lot of access to their data via published dashboards. Our user base within our company has been very happy with it and our user base is growing all the time and providing valuable input into what they would like to see in new dashboard visualizations.
It is particularly well suited for accessing reasonable denormalized Oracle database data, however it does equally well when accessing data in spreadsheets or other standard formats. The key question to ask would be how normalized is the data which the user wants to access, and if highly normalized whether some tables will need to be denormalized via new tables or views. It is also well suited organizations where there are a few super-users who can gather analytical and visualization requirements and then make these available to users of the information in the form of published dashboards. This works very well and keeps the total cost of ownership at a very reasonable level.

Tableau Desktop Feature Ratings

Pixel Perfect reports
Customizable dashboards
Report Formatting Templates
Not Rated
Drill-down analysis
Formatting capabilities
Integration with R or other statistical packages
Report sharing and collaboration

Using Tableau Desktop

Most of the user interface and usability is completely intuitive. It makes one look like they are a better analytics designer than they really are. The ability to connect easily to a wide variety of data sources without needing an interim extract, universe or catalog is a massive time and aggravation saver.
Like to use
Relatively simple
Easy to use
Technical support not required
Well integrated
Quick to learn
Feel confident using
  • Connecting to a data source
  • Using filters
  • Creating parameters
  • Easily able to create new visualizations using the "Show Me" tab
  • Placement of items in a dashboard, particularly when exact coordinates are needed or attempting to duplicate a look and feel

Tableau Desktop Reliability

Tableau Desktop's performance is solid. You can really dig into a large dataset in the form of a spreadsheet, and it exhibits similarly good performance when accessing a moderately sized Oracle database. I noticed that with Tableau Desktop 9.3, the performance using a spreadsheet started to slow around 75K rows by about 60 columns. This was easily remedied by creating an extract and pushing it to Tableau Server, where performance went to lightning fast.