Visual Analytics is the visual representation of data for analytic purposes. Now that there is an almost tautological definition, the next few paragraphs are going to provide a more functional understanding. Continue reading What Is Visual Analytics?
In both personal and professional lives it can be helpful to set goals for in order to achieve things as small as learning to change your windshield wipers to as large as starting a successful business. The problem comes when you need to keep track of those changes, and really see how you are progressing.
This Tableau dashboard is a simple way to dive into your goals in order to keep yourself on track.
Data processing is a topic that many new Tableau consumers struggle with. The biggest reason for this is because working with Tableau, and most other self-service analytic solutions today, requires a significantly different data structure than traditional business intelligence (BI) solutions. The reason for this is because modern solutions are designed to work directly with relational data stores, while traditional BI was a process of aggregation to allow humans to parse output data files.
The following is an example of how this change in data need can be deployed in a complex business environment.
Tableau has just been brought into Ice Cream Co., a company that is largely run as silos by each of its regions across the globe. The corporate inventory manager has decided to embrace Tableau and the regional managers are also on board. They now must with bring the topic to IT so that they can build the underlying data structure that will support the corporate and 5 US departments initially and foreign departments down the line.
The current environment has complex, and largely unknown to the business, processes that generate reports every month that each of the teams then filters up to decision makers so that Ice Cream Co.’s inventory levels stay in line with demand. Historically each of these processes, for each of the teams, needed to be built independently so that each team could do their reporting. This caused IT to develop and maintain near identical reports, queries, and data tables for each of the departments. So when IT was approached, they gave estimates of the development based on these historical procedures totaling 2 weeks per data source, per department.
Instead what is proposed is a single data source per type of data. You tell IT that you don’t need monthly reports to be generated anymore, because you are going to work with data in a more dynamic way. By creating a data table for current inventory, a second for orders, and a third for the production schedule, we can create a single data source for corporate that each of the departments will be able to use directly. Following the initial build, the only new development will be additional feeds coming into the system from the international departments when then come on board. This will shorten the development time for IT by removing their need to duplicate and maintain parallel systems so that they can focus solely on the new data source integration and the overall health of the data environment.
This proposal is possible because Tableau allows you to remove the need for report style output. Each of the departments work with similar data and when in a tidy data structure, see below, this allows each department to run analytics from a shared source. Additionally, because Tableau allows you to design dynamic dashboards, reporting efforts can be reduced and standardized. This removes a significant amount of repetitive manual work from the analysts so that they can work on identifying ways to improve the business.
“Tidy”, “denormalized”, “computer friendly”, or “tall” data refers to a data structure where each column has a unique set of information. Tidy data is not often human friendly, and thus, not common in most traditional BI applications. Tidy data works well with solutions like Tableau because it is structured in a way that is very computer friendly, it is also often how data is stored in databases because it allows for solutions to be more permanent.
The opposite of tidy data is “normalized”, “human friendly”, or “wide” data. This is often discussed as being highly readable and user friendly, because there is a conceptual line of data that can be read across. Data tables in traditional reporting are commonly presented as normalized data.
Examples of both of these two data structures are below.
Gallons on Hand
As a Tableau consultant my clients have brought me many unusual behaviors, normally I can explain it away with a simple explanation of how the software works, or a quick look around a few blogs or the Tableau Forums. However, a recent issue had me spinning my wheels because none of the usual suspects were the cause, and there wasn’t even a mention of the problem in the community.
On a dashboard being released to the first round of testers they were receiving the Tablet device view instead of the desktop view.
This issue was only happening on some people’s computers, of a group of 20 testers it was only happening on 4 computers, and one of those was the trainer’s computer.
The obvious (but wrong) answer:
I had them check their screen resolution and all of them we significantly larger than 800 pixels tall or wide (The value that changes the display from desktop to tablet view.)
The actual solution:
The obvious answer was on the right track but not the cause of the issue. As it turns out Tableau uses the pixel size of the web browser, at the zoom level you are viewing the page at, to determine which device view you are going to receive.
I ended up creating a simple dashboard on Tableau Public that just displayed one of three text boxes based on the device type being displayed. That dashboard can be found at the following link:
The following are screen shots at different levels of zoom demonstrating the issue.
Dynamic Parameters are one of the most widely requested feature updates in Tableau followed immediately by Multi-Select Parameters. If these are functionality you need then it can seem like tableau has backed you into a corner with no way out.
However, there are a few tricks that you can employ in order to achieve the desired effect. Continue reading Tableau Dynamic And Multi-Select Parameters
Let me start by saying that while this is a professional blog, I would like it to take on a somewhat informal tone. I would like to encourage discussion, and even potentially debates about what is posted here.
What/Who is A Transition In Thought?
A Transition in Thought is a BI consulting company with a focus in Tableau and Alteryx, data dashboarding and data blending/ advanced analytics software companies respectively. A Transition in Thought performs consulting and teaching services. If you are interested please contact Michael at email@example.com A Transition in Thought’s name come from two places. The first being that BI industry is undergoing a major transformation due in part to the shear power modern computing as well as the ever broadening acceptance of Visual Analytics, these changes demand a shift in thinking. The second being the CEO’s belief that the only way for progress happens is when we keep an open mind and allow new information and new perspectives to continue to mold the way we think. Thus A Transition in Thought.
A Transition in Thought LLC is a company independently owned and operated by Michael Davis (me). I received my BS in Mathematics from Hofstra University in 2012 and have been working in Analytics since. If you are interested in learning more about my professional career feel free to check out my linkedin. I would happily identify as a data geek but am much worse than that. I look at visuals I see in every day life and can’t help but think about how the data must be structured, what the questions must have been to develop the image displayed, how I would have designed the information display differently, what the goal of the image is, and so on. When I am not distracted by the information design around me, I enjoy cooking and learning about the way others view the world so that I can continue to broaden my own.
What should you expect?
The intention of this blog is to provide a forum for discussion about topics of interest that impact the BI world. I will be making periodic blog posts about Tableau and Alteryx related topics often showing how to build an interesting visual, prepare data, or discuss a solution I found for interesting problems.
How to Contact Me
Discussing a post?: Comments on it!
Looking for some help?: Send me an email at firstname.lastname@example.org I may not be able to respond immediately but it is the best way to make sure that I get your message.