Tableau Basics: Data Vis with Fulcrum

22 July 2015 by Katrina Engelsted

What happens after you have set up your app and collected information in the field? What is the best way to explore your data in a consistent and comprehensive manner? How do you make data more enjoyable to study?

There are a number of tools to get a solid grasp on the patterns of your data. These tools are classified as data visualization or business intelligence (BI) libraries and/or platforms. Today, we will explore the basics of Tableau, one of the leading business analytics & intelligence platforms on the market.

Tableau is a platform that has piqued my curiosity for a few months. The software is in a similar style to Excel– with tabs to move through different sheets. It aims to allow users to interpret and to tell stories with their data with little to no coding. You can read more about the software, its weaknesses and its strengths here.

Case Study: Tree Management in Denver

Using data visualization software, I wanted to learn three things about the trees managed by the Department of Parks and Recreation in the City and County of Denver:

  • How many trees are they managing?
  • Which is the break down of the types of trees that they are managing?
  • Where are the trees located?

To answer these questions, I downloaded Tableau Public and started exploring:

Workflow

  1. Export data from Fulcrum:

    • Login to Fulcrum and click on your app.
    • Click ‘data share’ on the central navigation tabs.
    • Choose CSV tab and click the link to download the records in to CSV data.
  2. Upload that CSV file to Tableau platform as Text File.
  3. Review the table that was uploaded in Data Source sheet. Make sure latitude and longitude columns are properly linked as ‘Geographic Roles’.
  4. Head to the Sheet 1 tab on the bottom and start creating the visualization.
  5. Drag and drop columns from the data into rows/columns on the visualization cards in the middle of the sheet. For maps, click the ‘map’ icon on the right dashboard and drag the ‘lat’ to rows and the ‘lng’ to columns.

My experience

After I uploaded a CSV file to Tableau, I was a tiny bit confused about what to do next. And so I got back online and looked through some of the guides. There is a lot of information out there on using Tableau– almost a little overwhelming. The community of users is large and seems to be very passionate about the platform. The big thing about using Tableau is to remember that it is meant to mimic Excel– so all I had to do was click on the bottom tabs.

Once I got into the worksheet, dragging and dropping the columns and rows was fun and easy. The drag and drop is where Tableau shines. Once you have all of your data (and it is organized consistently), it is quick to pop out charts, maps and histograms. I enjoyed trying different types of visualizations.

While using the map visualizations I learned that there are options for adding custom basemaps and USA census data (by county, which makes it limiting not only by country but by scale). Overall, it feels as if I have only touched the tip of the iceberg of Tableau software.

Results:

There are 108,923 trees managed around Denver. Pine, Ash, Maple and Locust trees are the most common trees maintained by the city of Denver. Most of the trees are located in residential neighborhoods east of the downtown area.

Source: Denver gov

Bottom Line

Tableau is powerful. It makes viewing data easier than an excel chart or poorly-done visualization. The best part is that you do not have to jump into code to create a custom visualization. This software allows you to create a variety of charts through dragging and dropping. I recommend it to any customer.

There were a few weaknesses I encountered on my exploration of the software: cartography and guides. It is difficult to make maps functional, flexible and beautiful. I think Tableau has done a good job at making a solid mapping visualization. The weakness on the maps is the cartography, such as the pop-ups and the difficulty with customizing the color schemes. A number of the color palettes did not seem color-blind friendly.

It took me a while to navigate through the guides, API docs and customization options. I think there is a lot of potential for automation and integration but it takes a lot of key-word searching and filtering.

Overall, Tableau is a good option for showing data on maps and in reports. I think that it is worth creating a script to automate data from Fulcrum in to Tableau for clients. I will have to freshen up on my Python and Java.

Next time… How do you begin to visualize something more technical or complicated? How do you show records with relationships to one another? How can you automatically pull in data from Fulcrum? What is the best way to export data? Can you do all of this at an affordable price?

Stay tuned in the next month for more explorations with this platform.

About the author

Katrina works with clients to help make Fulcrum work with their workflows. She loves talking tech, design and maps.

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