My friend and data visualization colleague Jon Schwabish wrote an interesting post today about Disclosure Rules for the Data Visualization Community. I actually fall into every category Jon describes, so I thought I would write a quick post about my thoughts on this subject and provide you with my "disclosure".
1.) I use Tableau at the University of Cincinnati in my data viz course. We've used it since the inception of the course. Tableau offers Tableau Public as a free platform, but in addition, they also offer a free academic license of Tableau Desktop for each class (all students in the class) and a free one-year license to any full time student. In other words, there is no financial gain to be made by promoting the use of Tableau in academic circles. Sure, they may go out in the world and promote it in their new job, but that would be their decision.
2.) We use Tableau at our company. Any company that invests in technology has to make a purchasing decision. Our company went from Microsoft reporting services to Cognos and then to Tableau. In each case, we chose what we determined to be the best platform at the time and each time we looked at most available tools on the market. If something comes along that is better for us then we would consider, but the company makes a big investment in these technologies so switching from one to another is not something we would do without a serious need or want for improvement. In the case of our Tableau purchasing decision (Desktop and Server), we decided on Tableau long before Tableau was a publicly traded stock.
3.) I'm a shareholder. I purchased my first Tableau stock in 2013 and have purchased some more shares each year. I've purchased as high as $102 and most recently at $43. I have never sold any shares, even when my shares hit $127 in July. Personally, I think the market overreacted to the soft quarter. I actually prefer to buy stocks that are solid companies and down on some sort of bad news (the same reason I also bought Chipotle). Tableau has no debt and $800 million in cash, so $11 of their stock price right now is cash. Their growth year over year is still very strong, even if it's not what the analysts expected. They also continue to lead in the Gartner 2016 BI rankings.
The Future of Tableau
As for the future of Tableau, I believe it is still the best data visualization and business intelligence software on the market today. Local companies seem to agree as well. I conducted two Tableau Training workshops last month. Both were sold out to capacity and I am scheduling two more in the months ahead with the same outlook. Demand for training is very high. Many of the major companies in the Cincinnati area are increasing their use of Tableau and switching from other BI platform over to Tableau. Another great indicator is the amazing Tableau community as evidenced by their tremendous conference growth year after year. Tableau, like R, has a vibrant community supporting the tool. Hundreds of blogs, forums and on-line resources with more and more coming out each day. In contrast, someone contacted a few months back about doing Lumira training at their company and I had absolutely no luck finding someone in the Cincinnati area to conduct the training for him.
Take a look at this chart from Google Trends comparing Tableau, Qlik, MicroStrategy, Cognos and Power BI. Try searching on your own, comparing companies and search terms for Tableau, Lumira, Spotfire, Power BI, Qlik, Cognos, Birst, Domo, etc.
Over the years and in many presentations and workshops, I have publicly stated my opinion of technology trends. Here's a summary below of a few things that I think will continue to trend in the field of data visualization and analytics.
1. Tableau - It's the market leader and will continue to be so in the foreseeable future.
2. R - R will continue to become the default platform for analytics. I believe SAS will die a slow death over many years. I shake my head on this one a bit, because it was only a year ago that I had a heated debate at one of my data mining workshops with someone who was a die hard SAS user. I'm sure it will take time for large organizations using SAS to migrate to R, but I've seen it over and over. This is not to say that SAS is bad. It's actually very powerful as well. However, with the power and cost of R (free), I believe it will continue to grow and dominate. It's hard to compete with free, especially if you are charging lots of money. Even Microsoft has put their stamp on this by acquiring Revolution Analytics and integrating R in SQL Server.
3. Python - will continue to grow as a coding language for data science. Like R, there are lots of packages and modules out there and a large community of support.
4. Alteryx - This is very powerful software with lots of built-in capability and the added benefit of using R for analytics and exporting directly to Tableau for visualization. Take a look at the trend over the last few years on the Gartner BI Report.
5. Power BI - Will become a strong platform in the market because it is a natural extension of the biggest "analytics tool" on the planet, Microsoft Excel.
6. Multi-core and GPU Computing - Platforms will continue to leverage the amazing capabilities of not just multi-core, but GPU computing. I believe this will ultimately influence tool choices as well.
7. D3.js - Truly the most versatile platform, but requires significant coding for visualization. Mike Bostock recently left the NY Times, so I can't wait to see what the future holds for D3 and derivatives (or other things he might come up with).
I could add virtual servers (ex. VMware) and Flash Storage (ex. Nimble) to the list. Both have made a transformational impact to our company's technology stack, but then I might be inclined to continue down the path to autonomous cars and drones, so I'll stop here.
I hope you find this information useful. If you have any questions feel free to email me at Jeff@DataPlusScience.com
