More Uses for Sets in Tableau

Today, we will talk about more uses for "Sets" in Tableau.  If you don't know what sets are, I recommend you read my previous post, Working with Sets in Tableau.  As usual, we will use the Superstore Sales sample data set in Tableau.

Scenario 1: Creating combinations of fields

Let's say you want to filter out values where "Category = Furniture" and "Region = Central."  You can create a set using "Category" and "Region", then filter the set based on that unique combination of values.  An example of this is as follows:

Step 1:

• Create the set

Set of Category and Region

I'm not sure what affects the ordering of the fields in the set.  I do know that dragging them around in the "Create Set" window has no effect on its display.  If you don't initially get the ordering you want, keep creating sets until you get the ordering you want.  Make sure to delete all of the extra sets.  If anyone knows how to change the ordering, please comment.  I'd love to find out why.

Step 2:

• Filter the value

Filter on Category and Region

Now, you will see that there are no values for "Furniture, Central" in the chart.

Sales by Category and Region (without Furniture, Central)

Scenario 2: Saving a subset of data

Imagine that your data is quite complex and you only want to look at a particular subset.  You could create a global filter for this, but that would affect all of your graphs.  So, let's create a set which stores a particular subset of the data.

Step 1:

• Choose your fields.
• Apply the filter condition you want, e.g. "Top 10"

Top 10 Products by Total Sales

Now, instead of dragging "Product Name" onto all of your charts, you can simply drag the set onto it.  I also read somewhere that using sets is more computationally efficient than using filters.  I do not know why this is, but I've tested it and it seems to be true.

I hope you found this informative.  Feel free to comment if you have any questions/suggestions.  Thanks for reading.

Brad Llewellyn

Associate Consultant

Mariner, LLC

llewellyn.wb@gmail.com
https://www.linkedin.com/in/bradllewellyn

Basic Coloring in Tableau

Today, we'll talk about using colors to spice up your graphs in Tableau.  Colors are the easiest attribute for people to recognize.  You can have a graph with 3, 4, or 5 different colors; and each of them would be easily distinguishable at a glance.  We would be fools if we did not exploit this.  As usual, we will use the Superstore Sales sample data set in Tableau.

Step 1: Create a worksheet.

Profit Ratio by Sub-Category and Region

Step 2: Decide what you want to show with color

This text table is rather large and it's difficult to see what's important.  We can use color to show values that are important against those that are not.  We can use the typical negative versus positive scale to determine the areas that are profitable versus the areas that are not.

Step 3: Determine the vessel for your color

It is extremely easy to color a text table, you just drag "Profit Ratio" to the "Color" Shelf.  However, coloring in text tables is not easy to see, so why do it at all?

Text Table with Red-Green Coloring

So which areas are unprofitable?  Most of them are grayed out.  This doesn't help much.  In fact, it would be almost completely useless if the user was colorblind.

We can see three distinct issues here.  First, the text is not a very good vessel for the color.  Second, the continuous scale causes most values to be gray.  Finally, the color scale is unusable for colorblind people.  Let's fix these.

Step 4:

• Change the "Mark Type" to "Square"
• Right-Click on the Color Legend, Select "Edit Color"
• Change the Palette to "Orange-Blue Diverging"
• Check the "Stepped Color" Box and Type "5" in the "Steps" Box
• Right-Click on any Square on the graph and Select "Format"
• Under "Default -> Alightment -> Horizontal", Select the "Right Align" Option
• Adjust the Column Width so that the Values do not overlap the Squares

Heat Map

This is what is referred to as a "Heat Map."  It is my favorite tool for quickly displaying differences across a single measure.  There's so much more that can be done.  Try creating Custom Color Palettes or using different shapes or background colors.  Thanks for reading.

Brad Llewellyn

Associate Consultant

Mariner, LLC

llewellyn.wb@gmail.com
https://www.linkedin.com/in/bradllewellyn

Issues Publishing Workbooks to Tableau Server

Today, let's talk about a couple of issues I've run into while publishing workbooks to Tableau Server.  As with all projects, the most important part is the delivery.  If the client never sees the product you slaved over, then what good did it do?  Tableau Server is a great mechanism for this.  You can work via Tableau Desktop on your local machine, and just publish them to Tableau Server.

Issue 1:  Include External Files

If your workbook runs off of a local extract, you will have to publish the extract to the server as well in order to have any data.  However, I was unaware that this applied to Custom Geocoding as well.  My workbook did not run off of a local extract, so I didn't see the need to include any external files.  I was wrong.  When I attempted to look at the workbook on the server, I would get an error and none of the graphs would display.  It turns out that "Include External Files" applies to local extracts as well as custom geocoding.  I haven't found a case where it was disadvantageous to check this box.  If you have, feel free to comment.

Issue 2: Packaging the Workbook

I had a worksheet with no external files that ran perfectly on my local machine.  However, when I published it to the Tableau Server, I would get an error saying "Field is invalid" and nothing would display.  Through trial and error, I found that the field was a necessary Date field.  Finally, I discovered that packaging the workbook would fix the problem.  I'm still curious as to why this is.  Needless to say, I always package my workbooks before I publish.

Issue 3: "Ghost" Columns

Once, I ran into an issue where I had an invalid field that was not appearing in Tableau Desktop, yet was causing an error on Tableau Server.  The error said something like "[Calculation_280932] is invalid."  I found a solution on a forum that I've forgotten how to find (Sorry to whoever wrote that, I wish I could credit you).  First, make sure there are no hidden fields in Tableau Desktop.  If you open the Tableau Workbook using Notepad, or some other rudimentary text-editing software, you can look at the XML code defining the workbook.  If you search for "hidden", you may find that there is a column that is labeled as hidden, even though it wasn't visible to Tableau Desktop.  If you delete this column, everywhere else it is called, and any syntax it leaves behind, you will have effectively eliminated it from the workbook.  Now, you can publish the workbook with no issues.  I HIGHLY recommend saving a copy of the workbook before you edit the XML code.  It would be very unfortunate if you broke your workbook with no way of repairing it.

I hope you found this informative.  If you have encountered any publishing issues and would like to share, feel free to comment.  Thanks for reading.

Brad Llewellyn

Associate Consultant

Mariner, LLC

llewellyn.wb@gmail.com
https://www.linkedin.com/in/bradllewellyn

Ways to Improve Performance in Tableau

Today, we will talk about various ways to improve the performance of your Tableau dashboards.  I recently worked on a project with a company that did not invest much into their server.  Therefore, they were handicapped by query speed and visualization performance.  However, that's not a problem for us, is it?  We are professionals.  So, let's look at some of the methods that can be used to squeeze as much as possible out of a small system.

Step 1:

• Use an extract.

There is nothing else that comes close to the efficiency gained using an extract.  If you don't absolutely need live data, extracting is the best bet.

Step 2:

• Limit your dashboard to fully answering only one scenario.

At it's simplest, a dashboard should be able to fully explore a single scenario.  If your dashboard has six sheets, five actions, and 3 quick filters, you might not be looking at only one scenario.  Remember, no matter how elegant and comprehensive your solution is, if it doesn't run as quickly as the user would like it to, he or she will not use it.  I would not recommend butchering your dashboard so heavily that it cannot fully handle a scenario.  If the user has to go somewhere else to find the answer, why did they use your dashboard at all?

Step 3:

• Limit the data being introduced to each worksheet.

If you are not planning on using a set of rows, you should filter them out of the data set as early as possible.  If your table contains all sales, and you only want to look at US sales, create a Custom SQL query that filters it out.  If the filter is worksheet dependent, try using a Context Filter.  For more information on filtering, check out my other post Types of Filters in Tableau.  You can also click the Down Arrow beside the word "Dimension" and Select "Hide All Unused Fields" to hide any fields you are not using in any of your worksheets.  I'm not sure if this improves efficiency; but I'd have to imagine that it does, less data should always improve performance.

Step 4:

• Remove components that add no value.

While aesthetics are very important to building a usable dashboard, unimportant objects aren't worth losing efficiency over.  In fact, you would be better off adding more functionality than you would by adding a purely aesthetic object.

Step 5:

• Eliminate any non-essential components from the visualization.

This refers to values that would appear on the Pages, Filters, and Level of Detail Shelves.  If they are purely there for the user to see if they scroll over a point, then they aren't adding any value to the initial glance.  However, I leave this as the last step because it should be a last resort.

In most cases, a little forethought can save you a lot of heartache when you are creating dashboards.  Decide exactly what story you want to tell, and tell only that.  It is much easier to add functionality to a small dashboard, than to butcher a large one.  Thanks for reading.

Brad Llewellyn

Associate Consultant

Mariner, LLC

llewellyn.wb@gmail.com
https://www.linkedin.com/in/bradllewellyn

Basic Dashboard Formatting in Tableau

Today, we will look at basic ways to format your dashboards to increase usability and improve interpretation.  The goal of a "perfect" dashboard is to alert a user to a situation and give them all of the information they need to act based on that alert.  For example, a Store Manager would be alerted that sales were low last week and be able to easily see that sales were down because Bananas did not sell well.  Therefore, he will go speak to his Produce Manager.

This is quite a lofty goal.  In fact, it's virtually impossible to display all of the information needed to make a decision.  Therefore, we should strive to display as much information as possible, while still maintain usability and performance.  Let's create a simple scenario to discuss a few points.  As usual, we will use the Superstore Sales sample data set in Tableau.

Scenario:

You are the US Manager for SuperStore.  Your are looking at this dashboard to make sure that your business is profitable.  The first sheet you look at it is a map of the US, colored by profit.

Profit Map

Uh oh.  Montana's not very profitable.  Let's pull up Profit by Sub-Category in Montana to see which Sub-Category isn't making money.

Profit by Sub-Category

Ah Hah.  Office Machines are losing huge amounts of money.  Let's look at Office Machine orders by Customer to see if this is widespread.

Profit and Discount by Customer

Turns out this was caused by one customer.  We can either click on this point to drill to the underlying data, or we can look her name up in our source system.  Either way, this was a lot of work in Tableau.  I wish we had a dashboard to do this.  HEY!!! Let's do that.

Step 1:

• Drag the sheets onto the workbook

This is nice.  However, it needs actions to link it.  In the above scenario, we had two steps.  First, seeing a red State should lead us to the Sub-Categories.  Second, seeing a red Sub-Category should lead us to the Customers.  Also, we don't want to bombard the user with useless information.  So, let's make two filter actions that activate on click, with no information displayed beforehand.

Step 2:

• Create the following two actions

Filter by State

Filter by Sub-Category

The keys to these filters are the "Exclude all values" button and the fields that are being carried over.  Notice that State is being carried over in the second filter as well.  This means that we had to add State to the level of detail on the "Profit by Sub-Categories" Sheet.  Now, we have a usable dashboard with actions.  However, we can still do a little more to make it look better.

Dashboard with Actions

Step 3:

• Remove the Color Legend.  It only maps to one graph and the extremity of the colors is of little importance in this scenario.
• Make sure that all three graphs are set to "Entire View".  If you don't know what this means, it's located in a drop-box at the top of the screen.  The other options here "Normal", "Fit Width", and "Fit Height."
• Right-click on the word "Category" in the "Profit by Sub-Categories" chart, then Select "Hide Field Labels for Rows."  The manager knows that "Furniture" is a "Category", we don't need to waste space to tell him that.

Dashboard with Complete Formatting

Great job!!! You've created a dashboard that you're boss can use to solve his problems.  You're definitely in for a raise.  Thanks for reading.

Brad Llewellyn

Associate Consultant

Mariner, LLC

llewellyn.wb@gmail.com
https://www.linkedin.com/in/bradllewellyn

Types of Filters in Tableau

In Tableau, there are three types of filters.  More explicitly, there are three different ways to limit the data that is displayed by your graph.  These types are Custom SQL "Filters", Context Filters, and Traditional Filters.  Each of these has its own strengths and weaknesses, and we will look at them one at a time.

First, a Custom SQL "Filter" is a WHERE clause that is placed in the SQL that queries the data to be used in the workbook.  "Filter" is a Tableau term that technically applies only to Context and Traditional Filters; however, the Custom SQL "Filter" emulates the behavior of a global Context Filter, so we will refer to it as such.  By construction, Custom SQL "Filters" are always global.  The most common reason for using a Custom SQL "Filter" is to limit the size of a data extract.  The smaller your data extract, the more quickly your charts will load.  In other words, you can make more complex charts without sacrificing efficiency.

One of the ways to create a Custom SQL "Filter" is during the Server Connection process.  For example, here I create a new SQL Server Connection.

SQL Server Connection

Once I select the Server and Database I would like to use, I can select the table(s).  I can use either the Single Table or Multiple Tables feature to select the table, then I can click on the Custom SQL button.

Custom SQL Server Connection

In the SQL code, I can place a WHERE clause to filter on any values I would like.  This is the most efficient of all filters.  If you would like to place a static, global filter on your data, this is where you should do it.

Next, a Context Filter is a filter in Tableau that affects the data that is transferred to each individual worksheet.  Context Filters are great when you want to limit the data seen by the worksheet.  When a worksheet queries the data source, it creates a temporary, flat table that is uses to compute the chart.  This temporary table includes all values that are not filtered out by either the Custom SQL or the Context Filter.  Just like with Custom SQL "Filters", your goal is to make this temporary table as small as possible.

Context Filters have a few advantages over Traditional Filters.  First, they execute more quickly than Traditional Filters.  They are also executed before Traditional Filters and can be executed all at once, which further improves efficiency.  However, they do have one drawback.  It takes time for the filter to be placed into context.  A rule of thumb, from Tableau's KnowledgeBase, is to only place a filter into context if it reduces the data by at least 10%.

A Context Filter is created by dragging a field onto the "Filters" Shelf and editing the filter.  Then, you can Right-Click the field on the shelf and select "Add to Context."  If you have multiple context filters, you can CTRL-Select them all and add them to context in a batch.  This will improve the efficiency of your filter.

Lastly, a Traditional Filter is exactly what most people think of when they think of filters.  When Tableau is creating the visualization, it will check to see if a value is filtered out by a Traditional Filter.  Since this is not performed at the table level, it is the slowest of all filter types.  However, it does have the advantage of being performed after the Context Filters.  This is a necessity if you are dealing with complex "Top N" filters.  A Traditional Filter can be created by simply dragging a field onto the "Filters" Shelf.

EDIT: If you would like to know more about the order in which Traditional Filters are processed.  Check out this link submitted by Jonathan Drummey:

 http://community.tableausoftware.com/message/139603#139603

(Jonathan's Google+)
https://plus.google.com/114523841892404322313

I hope you found this post to be informative.  Thanks for reading.

Brad Llewellyn

Associate Consultant

Mariner, LLC

llewellyn.wb@gmail.com
https://www.linkedin.com/in/bradllewellyn

Different Types of Graphs in Tableau

Today, we will look at a few different types of graphs in Tableau.  More specifically, we will look at the options within the "Marks" Card.  As usual, we will use the Superstore Sales sample data set in Tableau.

Type 1: Text Table

Text Table

Text Tables are definitely the simplest of charts in Tableau.  They contain no graphics at all.  Despite their simplicity, they excel at displaying multiple measures simultaneously.  In the above chart, I easily displayed five measures without cluttering the screen.  Text tables also display much more quickly due to their non-existent graphics.

Type 2: Bar Graph

Bar Graph

Bar Graphs, sometimes improperly referred to Histograms, are great for displaying a small number of measures across one or two dimensions.  The stacked bar graph above gives an easily interpreted view of Sales across Region and Category.  Bar Graphs display somewhat more quickly as well, due to their visual simplicity.

Type 3: Line Graph

Line Graph

Line Graphs are somewhat similar to bar graphs in their interpretation.  There is one minor difference.  In a bar graph, it is difficult to detect differences in size across a single color due to the bar being located in different places.  A line graph does not have this limitation due to the fact that the values are linked via a line.  However, line graphs typically denote some sort of ordering, usually time.  It is unwise to use a line graph when your dimension has no innate ordering (That's what a bar graph is for).

Type 4: Area Graph

Area Graph

An area graph is pretty much a mix of a line and a bar graph.  It is a line graph where all of the area below the line is shaded.  While this is pretty much a waste of space in most applications, I find it useful when combined with the "Bin" feature to create a probabilistic function.  However, if you were to switch this graph from an area graph to a bar graph, it will maintain it readability and become something people have seen before (This is the description of an actual histogram).  Alas, I like this view.

Type 5: Shape Tables

Shape Graph

Shape graphs are the broadest range of graphs.  They allow you to place pretty much any shape you want, wherever you want, while also giving it dynamic sizes and colors to allow easy interpretation.  The graph above is called a heat map.  It allows the user to see, at a glance, which values are high and which values are low.  Shape graphs are my favorite in my most applications.  However, due to their complexity, they tend to display more slowly than other types of graphs.

Type 6: Pie Chart

Pie Chart

The pie chart may be the most universal of graphical charts.  It is widely known exactly how to interpret these.  They are also rejected by most visualization experts due to their lack of space efficiency and their limitation of only being able to display a single concept.  The above chart is the best example I could come up with as to how to use a pie chart.  Alas, I still feel this information would be better displayed in some other form, like a Heat Map.

Type 7: Gantt Bar Graph

Gantt Bar Graph

A Gantt Bar Graph is similar to a line graph, but the points don't connect.  So far, I've yet to see someone up with a good use for one.  However, I will keep my eyes open.  Maybe there's a hidden use for them that I'm missing?

Type 8: Filled Map

Filled Map

A filled map is a great way to display geographic data.  It's pretty much a heat map superimposed on an actual map.  With Tableau's abilities to generate all kinds of maps, as well as allow custom maps, this could be the best of the basic display tools.  If you have geographic data, I highly recommend using some type of filled map.

Type 9: Polygon

Polygon

This is an interesting concept that Tableau implemented.  This is not a graph "per se."  It is more of a visualization tool.  Tableau allows you to create your own coordinates and superimpose them on an image.  Therefore, with enough time and effort, you would create some incredibly detailed visuals with this tool.

I hope you found this introduction to be enlightening.  Thanks for reading.

Brad Llewellyn

Associate Consultant

Mariner, LLC

llewellyn.wb@gmail.com
https://www.linkedin.com/in/bradllewellyn

Working with Quick Filters in Tableau

Before we start with the post, I would like to mention a change in terminology that I hope doesn't confuse too many people.  What I had previously been calling "Panes" are actually called "Shelves."  In Tableau, a "Pane" refers to a specific combination of a row field and column field.  From now on, they will be referred to as "Shelves."  I apologize for any confusion this may cause.

Now, on with the post.  Today, we will look at "Quick Filters" in Tableau.  A Quick Filter is nothing more than a regular filter that can be dynamically altered via a card on the screen.  Traditionally, you set a filter on the filter shelf and it's done.  If you want to change it, you have to open up the filter and change it there.  Quick Filters allow you to change the filter on the fly, which adds for quite a bit of simple user interaction.  Let's see an example where this comes in handy.  As usual, we will use the Superstore Sales sample data set in Tableau.

Step 1:

• Create a Worksheet

Order Quantity by Region

Step 2:

• Add "Category" to the "Filters" Shelf
• Select every "Category" in the filter.
• Right-Click on "Category", Select "Show Quick Filter"

Order Quantity by Region (with Category Quick Filter)

Now, you can select whichever Categories you want and your graph will be automatically filtered.  By clicking on the Arrow in the Top-Right Corner of the Quick Filter Card, you can change the way the Quick Filter works.  First, you can change whether the filter is applied to the database, context, or only relevant values (We'll discuss this more in a later post about different types of filters).  You can also change whether it is an inclusion or exclusion filters.  Lastly, you can change the way the card is displayed.  Quick filters are another one of the simple features of Tableau that adds an incredible amount of usability.  Finally, I will leave you with a more elaborate way to use a quick filter to emulate a page.

Step 3:

• Drag "Order Quantity" From the "Text" Shelf to the "Rows" Shelf
• Remove "Region" From the "Rows" Shelf
• Remove "Category" from the "Filters" Shelf
• Add "Order Date" to the "Filters" Shelf
• Select "Relative Date" from the Pop-Up Window
• Select the "Years" Box
• Set the "Anchor Date" to be any day in "2009"
• Select the "Next 3 Years" Bubble
• Show the Quick Filter

Order Quantity by Year (with Anchored Year Quick Filter)

Now, you can scroll through years just like you could with a page.  As you can see, there are an incredible number of possibilities if you use a little creativity when creating your visualizations.  You should try adding custom calculations and parameters to your filters.  Thanks for reading.

Brad Llewellyn

Associate Consultant

Mariner, LLC

llewellyn.wb@gmail.com
https://www.linkedin.com/in/bradllewellyn

Working with Pages in Tableau

Today, we will talk about the "Pages" feature in Tableau.  When you drag a field onto the "Pages" Pane, you get a separate graph for each value in the field.  You can then cycle through the values to create a sort of slideshow on your graph.  This is especially useful for showing how your data changes through time.  As usual, we will use the Superstore Sales sample data set in Tableau.

Step 1:

• Create a Worksheet

Sales by Region

Step 2:

• Drag "Order Date" onto the "Pages" Pane
• Uncheck the "Show History" Box

Sales by Region (with Yearly Pages)

While this is somewhat useful, it lacks any sense of history.  What if you need to see how this year's values compare to last year's?  "Pages" can do this as well.

Step 3:

• Keep "Order Date" In the "Pages" Pane
• In the "Page" Card (top-left where you select which year you want to look at), Check the "Show History" Box
• Add Another Instance of "Order Date" to the "Columns" Pane

Sales by Region and Year (with Yearly Pages)

Now, you can see the previous values as well.  One thing we haven't touched on yet is the ability to "Auto-Play" a set of pages.  On the "Page" Card, you can click the "Play" Button (looks like a Right-Arrow) to cause the pages to cycle through on their own.  You can alter the speed of the play by selecting on the boxes with the bars in them in the Bottom-Right corner of the "Pages" Card.  Also, if you click on the arrow in the Top-Right corner of the "Page" Card, you can set whether the play will loop or not.  So far, we've only been using text tables due to their simplicity; however, these tools can do so much more.  I encourage you to play around with the "Pages" tool and see what kinds of interested visualizations you can create.  Thanks for reading.

Brad Llewellyn

Associate Consultant

Mariner, LLC

llewellyn.wb@gmail.com
https://www.linkedin.com/in/bradllewellyn

Working with Parameters in Tableau

Today, we will look at the ways to use Parameters in Tableau.  Parameters are values that you can easily change on the fly to alter the look of any of your graphs.  Parameters are also unique in their ability to be constant across charts; this means that you only have to change the parameter once, and it can change all of your graphs.  First, let's create a parameter.  In order to create a parameter, you must have a place to use it.  As usual, we will use the Superstore Sales sample data set in Tableau.

Step 1:

• Create a Worksheet

Sales by City

An analyst might say "Whoa, there are so many cities.  I only want to see the cities where customers spend a lot, but I don't know how many I want."  This is where parameters come in.

Step 2:

• Open the filter window for "City"
• Under the "Top" Tab, Select "By Field"
• Select "Top", "Sales", "Sum" leaving the "Number" Box empty
• In the "Number" Box, Select "Create New Parameter"

Parameter Creation Window

In this window, we have quite a few options.  For a "Top N" case, we only want users to be able to select integers.  We also want to limit their choices to a small number.  So, let's create a parameter that ranges between 1 and 25, but defaults at 10.

Step 3:

• In the "Name" Box, Type "Top N"
• In the "Current Value" Box, Type "10"
• In the "Display Format" Box, Select "Automatic"
• Under "Allowable Values", Select the "Range" Bubble
• Under "Range of Values", Type "1", "25", "1"

Sales by Top N Cities

Now, you can change the value of the parameter in order to change the number of cities that you see.  You might also notice that, while the top N are being displayed, the data is not sorted in the manner.  This seems unusual.  You could easily go back and sort this data if you wanted.  Also, if you click the arrow in the Top-Right corner of the "Top N" Card, you can change the display style of the card.  Once a parameter is created, you can use it in your custom calculations as well.  With this, there are endless possibilities using parameters.  Thanks for reading.

Brad Llewellyn

Associate Consultant

Mariner, LLC

llewellyn.wb@gmail.com
https://www.linkedin.com/in/bradllewellyn

Sorting your Data in Tableau

Today, we will look at ways to sort your data in Tableau.  Sorting is a simple way to increase the effectiveness of your visualizations, especially when paired with other techniques, such as sets and filters.  Let's start by creating a simple sorting.  As usual, we will use the Sample Superstore sample data set in Tableau.

Step 1:

• Create a Worksheet

Total Shipping Cost by Container Type

By default, Tableau sorts the field values in data source order, starting with the first field.  This means that whichever value comes first in the data source, will come first in the graph.  This is not likely to be helpful for any of your business decisions.  So, let's sort the data from largest value to smallest value.

Step 2:

• Right-Click "Container" in the Rows Pane and Select "Sort..."
• Under "Sort Order", Select "Descending"
• Under "Sort By", Select "Field"
• Then, Select "Shipping Cost", "Sum"

Total Shipping Cost by Container Type (Sorted by Total Shipping Cost)

Now, we can see that "Container" in the Rows Pane has been Bolded.  This is how you can tell if a field has been sorted.  This sorting is quite simple.  Let's look at something more complex.  Let's sort the shipping costs based on how much Total Order Quantity they have, without displaying Total Order Quantity in the graph.

Step 3: 

• Open the "Sort" window for "Container"
• Under "Sort Order", Select "Descending"
• Under "Sort By", Select "Field", Then "Order Quantity", "Sum"

Total Shipping Cost by Container Type (Sorted by Total Quantity)

We can see that some items have moved higher up the list.  This is great because it allows us to see what container types contain cheaper items, without having to create a calculated field.  While sorting is simple in-and-of itself, it is an invaluable tool for increasing the effectiveness of your visualizations.  Thanks for reading.

Brad Llewellyn

Associate Consultant

Mariner, LLC

llewellyn.wb@gmail.com
https://www.linkedin.com/in/bradllewellyn

Working with Filters in Tableau

Today, we will look at how to create filters in Tableau.  Filters allow you to control the data that is displayed in your graphs.  As usual, we will use the Superstore Sales sample data set in Tableau.

Step 1:

• Create a Worksheet

Average Discount by Region

Let's say that we are the new manager for the South and East Regions, so we only want to see these only the graph.  We can accomplish this with a filter

Step 2:

• Right-Click "Region" in the Rows Pane and Select "Filter"
• Under the "General" Tab, Uncheck the boxes for "Central" and "West"

Average Discount by Region (South and East)

On the other hand, let's say we only want to see the Regions that end in "st", which in this case are East and West.  We can do that too.

Step 3:

• Drag "Region" off of the Filters Pane to remove the filter.
• Right-Click "Region" and Select "Filter"
• Under the "Wildcard" Tab, Select the "Ends With" Bubble.
• Type "st" in the Match Value Box.

Average Discount by Region (Ending in "st")

Now, what if we only wanted Regions that have an average discount of less than 5%.  That is just as simple

Step 4:

• Remove the "Region" filter.
• Open the filter window again for "Region"
• Under the "Condition" Tab, Select the "By Field" Bubble
• In the "Field" Box, Select "Discount"
• In the "Aggregation" Box, Select "Average"
• In the "Operator" Box, Select "<"
• In the "Value" Box, Type ".05"

Average Discount by Region (Less than 5%)

You may notice that we added another decimal place to the Discount Field to clarify that the values were in fact less than 5%.  This will be explained in a later post.  Finally, what if you only wanted to see the top 2 Regions?

Step 5:

• Clear the filters and reopen the filter window for "Region"
• Under the "Top" Tab, Select the "By Field" Bubble
• In the "Direction" Box, Select "Top"
• In the "Number" Box, Type "2"
• In the "Field" Box, Select "Discount"
• In the "Aggregation" Box, Select "Average"

Average Discount by Region (Top 2)

There are a myriad of possibilities when it comes to way you can filter your data in Tableau.  Don't be afraid to mess around and see what kinds of interesting ways you can discover.  Thanks for reading.

Brad Llewellyn

Associate Consultant

Mariner, LLC

llewellyn.wb@gmail.com
https://www.linkedin.com/in/bradllewellyn

Working with Sets in Tableau

Today, we will look at Tableau's "Sets" feature, which allows you to alter the data displayed in your graphs.  As usual, we will use the Superstore Sales sample data set in Tableau.

Step 1:

• Create a worksheet with 2 non-hierarchical fields

Profit by Region and Ship Mode

As you can see, we have a "Cartesian Product" of Region and Ship Mode.  This means that every combination of Region and Ship Mode exists.  But, what if we wanted the combination of these fields to be a single field instead of two.  In SQL, you could concatenate the fields together; however, tableau has a better way.

Step 2:

• CTRL-Select "Region" and "Ship Mode" in the Dimensions pane.  Both should be highlighted.
• Right-Click one of the Selected Fields and Select "Create Set"
• Type "Region and Ship Mode" in the Name Box
• Find the Set in the "Sets" Pane in the bottom-left corner
• Add this set to the graph

Profit by Region and Ship Mode, with Set

We see that every row has a distinct value in the set.  While this is merely cosmetic for this graph, you can now implement more complex filtering and sorting based on combinations of fields.  We will see many more great uses for this feature later.  Thanks for reading.

Brad Llewellyn

Associate Consultant

Mariner, LLC

llewellyn.wb@gmail.com
https://www.linkedin.com/in/bradllewellyn

Custom Calculations in Tableau

Today, we'll look at custom calculations in Tableau.  In my opinion, these are the most useful tools in Tableau's arsenal.  They can be used to calculate almost any value you would need, and can even be used in some clever ways to spice up your charts.  As usual, we will use the Superstore Sales sample data set in Tableau.

Step 1:

• Decide what value you want

Step 2:

• Select "Analysis -> Create Calculated Field..."

Here, you can peruse the list of functions in the bottom-right corner to see what kind of calculations you can create.  These calculations follow a simple rule, they are always calculated with respect to the cell they are in.  For instance, if your graph displays Profit by State, then SUM( [Profit] ) will be calculated for each state.  Let's create this field.

Step 3:

• Type "SUM( [Profit] )" into the Formula box.
• Type "Sum of Profit" into the Name box.

Step 4:

• Find the new Calculated Field in the Measures Pane.
• Create a Worksheet with this Field.

Profit by Sub-Category

You might be saying "Hey, we already had a Sum of Profit field by dragging Profit onto the chart!"  You're right, the default aggregation for Profit is Sum; so, dragging it onto the chart will give you exactly these values.  Now, let's get a little more complex (and useful) and create a new field that we don't have access to already.

Step 5:

• Create a Calculated Field named "Profit per Item"
• In the formula box, type "SUM( [Profit] ) / SUM( [Order Quantity] )"
• Add this Field to your Worksheet

Profit and Profit Per Item by Sub-Category

Now that you know how to create Calculated Fields, you can explore a whole new world inside Tableau.  Thanks for reading.

Brad Llewellyn

Associate Consultant

Mariner, LLC

llewellyn.wb@gmail.com
https://www.linkedin.com/in/bradllewellyn

Table Calculations in Tableau

Today, we'll look at what is arguably Tableau's most important feature, table calculations.  First, let's go through the steps of making a simple Table Calculation.  As usual, we will use the Superstore Sales sample data set from Tableau.

Step 1: 

• Create a Worksheet.

Profit by Region

Step 2: 

• Right-Click SUM(Profit) in the Text Pane
• Select "Quick Table Calculation -> Percent of Total"

Percent of Total Profit by Region

Congratulations, you've created your first table calculation.  Now, you can see which regions are the most profitable at a glance.  This is only the tip of the iceberg though.  There is much more that can be done here.  First, you can edit your table calculations to be more complex.  Let's revise our percent of total be able to handle a 2-dimensional table.

Step 3: 

• Add Another Dimension to the Worksheet

Percent of Total Profit (?) by Region and Category

Looking at this, we see that something isn't right, our percent of total is by column (Notice how each column adds up to 100%, but each row does not).  We want it to be for the entire table.

Step 4: 

• Right-Click the Table Calculation
• Select "Compute Using -> Table (Across then Down)"

Percent of Total Profit by Region and Category

There is so much more that can be done with Table Calculations.  Alas, we'll have to save that for another post.  Thanks for reading.

Brad Llewellyn

Associate Consultant

Mariner, LLC

llewellyn.wb@gmail.com
https://www.linkedin.com/in/bradllewellyn