When we talk about Tableau, many probably wonder if they should invest their hard-earned dollars or their company’s dollars in that technology.
Therefore, I took Tableau benefits and disadvantages out. Tableau is, without a doubt, the leader in data viz space.
There are some limitations, though, that could point you to another tool. When you compare Power BI or Qlikview there are a lot of options out there. See our post on 4 Tableau Alternatives for reference.
Tableau Text Mining at the Speed of Thought directly
How to perform Text Mining at the Speed of Thought directly in Tableau?
I was always tempted to reach out for a scripting language such as R , Python or Ruby while I was doing text mining with Tableau.
And then I’m feeding the results into Tableau. Tableau served as a communication tool to pleasantly portray the insights.
Wouldn’t it be useful to conduct text mining and deeper research directly in Tableau at the speed of thought?
Tableau has several fairly simple features for word processing that can be used for measured fields.
However, this is not enough to conduct text mining such as sentiment analysis, where splitting of text into tokens is necessary. The cherished incorporation of Tableau ‘s R certainly won’t help in this situation.
Reasons to Invest: Advantages of Tableau
- The visualisation of data with Tableau
Tableau is first and foremost a tool for data visualisation. Hence, it’s technology is there to help sophisticated computations, data mixing, and dashboarding to create stunning visualizations that offer information that can’t be simply obtained by looking at a spreadsheet. Due to its devotion to this mission, it has risen to the top of the data visualisation heap.
- Creating immersive visualisations quickly: The user will create a very dynamic visual within minutes by using Tableau’s drag-n-drop functionalities. The interface can handle endless variations while also limiting your ability to create charts that oppose best practices in data visualisation. You should check out some of the fantastic graphics that were produced at the Tableau Gallery.
- Implementation facile: Tableau offers many different types of visualization options which enhance the user experience. Even, similar to Python, Business Artifacts and Domo, Tableau is very easy to understand and someone without coding experience will quickly learn Tableau.
- Tableau can handle big data quantities: Tableau can easily handle millions of rows of data. With a large volume of data, various forms of visualization can be generated without impacting the Dashboard output. There’s also a Tableau option where the user can make “live” connections to various data sources such as SQL etc.
Usage of Tableau scripting languages other than
Users can incorporate Python or R to avoid the performance issues and to do complex table calculations in Tableau.
By performing data cleaning tasks with packages, the use of Python script can take the load off the software.
Python is not, however, a native scripting language which Tableau accepts. So, some of the visuals or packages you can import. You can see how Python has this down for Power BI, though.
Remote and Responsive Dashboard service
Tableau Dashboard has a nice monitoring feature that helps you to precisely configure the dashboard for a single computer, such as a cell phone or laptop.
Tableau also knows which computer the user is reading the report on and makes changes to ensure the right report is delivered on the appropriate device.
Company strategy tableau
Tableau did a great job climbing its way to the top of the tools for visualizing data. Therefore, Magic Quadrant according to Garner.
As a leader Tableau spent more than six years. Nonetheless, with the growing growth in data science, artificial intelligence , and machine learning, if it doesn’t evolve fast, Tableau could be left behind.
From the issues with 2017 financial reports, you can see Forbes’ concerns with the profitability of the Tableau
Reasons to Not Invest: Disadvantages to Tableau
And, now that you are aware of all the tool ‘s wonderful facets, let ‘s delve into some of the more difficult features. The segment below will illustrate some of the pressure points which are shared by several Tableau users.
- Scheduling and/or report notification:
Tableau with the help of scheduling does not provide the automatic refreshing feature of the reports. Tableau does not offer a scheduling option. Therefore, some manual work is often required when users need to upgrade the back-end info.
- No Visual Imports on Custom – Tableau isn’t a complete, usable tool. Unlike other tools such as Power BI, developers are able to create custom visuals that can easily be imported from Tableau. So, you have to recreate any new visuals instead of importing them.
- Tableau customized formatting: Conditional formatting of the tableau and limited display of the 16 column table are pain points for users. There is also no way a user would do this explicitly for all fields or apply the same formatting on different fields. For each area which is very time-consuming, users need to do it manually.
This is Tableau’s biggest issue, it’s a very expensive product to scale across a large organisation. Compared to BI tools which are cheaper and more rounded.
Tableau one of the costlier options. The only option for security and sharing is Tableau Server that can provide $175,000 for an 8-core option, and $35 per user.
Additionally, you can use the tiny, but $35 per month, Tableau Online. This can escalate while you are attempting to provide permission records for a significant number of users.