Archive for Tableau – Page 2

Top 5 New Features in Tableau 10

The beta version of Tableau 10 is currently out and I took some time out to review some of the new features of 10. There are a lot of great new features and a cleaner UI, but here are my top 5 favorite new features.

  1. One Click Revision History – Mistakes happen. For example, someone overwrites a workbook by accident or you want to revert to a previous version of a workbook. Unless you have the older version saved somewhere else, it used to be gone forever.  With 9.3 Tableau introduced version history, now they made it easier to preview and restore those previous versions.
  2. Device Specific Dashboards – Before you would need to create multiple versions of your dashboard if you wanted it to render correctly on multiple devices. Now you can publish a single dashboard that can have a different layout for desktop, tablet, or phone. Tableau will detect which device browser screen size and display the appropriate layout for that device.device specific
  3. Workbook Formatting – This one had me looking to the sky and yelling “Hallelujah!”   Rather than updating every single title and tooltip to the font style, color, and size that is set by your association’s style guide, you can now set this on the workbook level. Now each new worksheet and dashboard will have the styling you want.
    format workbook
  4. Cross Data Source Filtering – Previously, if you were working with multiple data sources and you wanted to have a filter that would work across those data sources, you had to do a workaround that involved parameters or actions. Now, you can use “All related data sources” and quickly be able to filter across data sources.
    cross ds filter
  5. Clustering – Say you want to be able to segment groups that are similar based on multiple attributes. Now with clustering, you will be able to do this. Let’s say, I want to find states that are similar to one another based on the percent of the population that does not exercise, smokes, diet, and obesity. I can now drag Cluster from the Analytics pane and through the magic of analytics it will determine which states are similar.

I am looking forward to all the new features that Tableau has added to 10. I believe it has really helped them deliver “Analytics at the speed of thought.”

Tableau 9.3: Smarter Version Control and Better Use of Color

Tableau 9.3 was released last week and has several exciting new features. These are a few of my favorites.

  1. Versioning.  In previous editions, when you published a workbook or data source to Tableau Server with the same name as something that already existed, you got a message asking if you’d like to overwrite the older file. “Of course I would,” I’d always say. But there are certainly times when seeing the previous version would have been helpful. Perhaps it would have also avoided some internal strife when a co-worker saved over my amazing workbook.versioning
  2. Publish data source flow. In this version, there is a newly designed dialog box to aid in publishing your data source more quickly. The most frequently used settings and options are available on the same screen. While seemingly small, what I am excited about is the option to “Update workbook to use the published data source.” This means that you can explore your data in Tableau Desktop while connected to the data source you just published. Previously, you had to publish the data source, connect to the data source from Tableau Server, then go through a replace data source process to connect to the published data source.
  3. Excluding totals from coloring. Totals, subtotals and grand totals can be excluded from color-encoding. What does that mean? Previously, if you wanted to do shading based on a count or sum and also wanted to show totals, the darkest color was always the total. This made it easy to overlook the items with the highest totals. Leaving the totals blank, the eye is drawn to 2014 female registrants instead of the grand total.totals coloring - oldtotals coloring - new
  4. Sheet colors. I love colors and I love organization. I’ve been using colors on sheet tabs for some time in Tableau Desktop to organize sheets based on data sources, the audiences or dashboards. Now, coloring is available on Tableau Server as well.sheet colors

How to Find the ‘WOW!’ Factor in Visualizations

When I review a new visualization, I’m always thinking it doesn’t have any wow factor. Here is a perfect example of something that gives an initial impression of WOW, but upon further review takes a lot of effort to understand.
effective_visualizations_busyThis was voted the fourth best Tableau Public “Viz of the Day” for 2015. When I’m building a visualization, I always look for pizzazz and pop right out of the gate. This one fits that bill. Visualizations need to be effective and not just eye candy, especially if you want to increase adoption and usage.
The first step to get there is to change your mindset. A few excellent suggestions from data enthusiast Joshua Burkhow will also help you see progress, with increased adoption and data driven decisions at your association. Here’s how to make it happen:

  1. Understand the end goal. This is specific to planning a deliverable as opposed to simply exploring data. Target the viewers and interactors of the dashboard. Talk to them and determine what they want to get out of it before you sit down to assemble the viz.
  2. Be iterative. Don’t expect perfection the first time through. Share it often and incorporate the feedback received.
  3. Drop the tables. For the most part, leave the datasheet tables off the viz. Yes, there is a time and place for them, but graphical representations are more effective for the brain.
  4. Enjoy some white space. Don’t overcrowd and put everything on one page. It will turn into the dashboard version of the garage who has no cars inside, but rows and rows of boxes instead. Just try to find something in there!
  5. Entertain with a story. This is a true story based on your data. Storytelling is really a separate topic on its own. Its point is to provide context and make it memorable.
  6. Mix it up a little. Repurposing and reusing is wonderful, but it isn’t always the best approach. Explore new visualizations. Maybe changing the look is a more effective way to see what the data is saying.
  7. BONUS: Aim for the masses. Each association professional will have a different opinion, so it might not be possible to incorporate everyone’s desires – certainly not on one visualization. Think of it like ice cream flavors. How many are there? Lots! Focus on the differences between vanilla and chocolate to please as many people as you can.

Here is an event demographic visualization I like it because it combines registration count, individual demographics, organization demographics, and a map.  It isn’t too busy and provides a quick breakdown of meeting attendees.

New Features in Tableau Server 9.2

Just in time for the holidays, unwrap the latest Tableau version available, 9.2, and install it for your association.  Staying current with Tableau Server is always a good idea:

  • avoid version conflicts by always matching the version of Desktop available from Tableau.
  • get the latest performance enhancements and bug fixes that are not always noted in new feature releases.
  • if you require support, you’ll always be asked to upgrade to the latest version.

The latest release also contains many new compelling features, including:

  1. Web Authoring – A powerful feature that enables licensed Tableau Server users to edit and create visualizations on the fly without a license for Desktop.  New features added here:
    • the ability to go directly to the sheet of a dashboard and manage data blends.
    • additional access to the data fields including the ability to update the data type.
    • access to formulas, including the ability to create a new one.
    • updated toolbar makes finding the mostly commonly used features easier and improves usability across screen sizes (see image below).
  2. Permissions – it’s now possible to set permissions at the project level. Previously they were inherited from Workbook and Data Source defaults. Administrators can also lock a project so authors cannot make any updates.
  3. Performance – Who doesn’t want their visualizations and dashboards to render faster?  Published workbooks take advantage of browser capabilities to display shape marks more quickly. Workbook legends are a little smarter to only redraw when visible changes are made. In addition, Tableau can cache more queries using its external query cache compression leading to leveraging a system’s RAM better.

The complete release notes and new features are here.  Schedule your install today.  If your IT vendor doesn’t directly support Tableau system updates, please contact us to discuss our Adoption Acceleration program which includes regular updates and maintenance.

Enabling the Analytic Workflow

Just as associations have a treasure of diverse data waiting to have a conversation, Tableau offers a variety of options for interacting with your organization’s data to enable association analytics.

  • Live data source connection – serves as a pass-through to a data mart or source systems that submits queries during interaction
  • Published data source – contains connection information that is independent of any workbook and can be used by multiple workbooks
  • Packaged workbook – encompasses data source connection information associated with a specific workbook

Data extracts leverage Tableau’s high-performance data engine that is based on VizQL, a technology that combines data querying and visualization,and does not require the limitation of
completely loading data into memory.  This means that business staff can efficiently explore data with fast responsiveness.
Published data sources can be used by multiple workbooks to benefit from consistent customized folders, field-level customizations, data hierarchies, calculated fields, dimension/measure assignments, and data selection criteria.  This ensures that any changes, such as the assignment of business-friendly names, will automatically be available to all visualizations and dashboards using the data source.  The underlying data is automatically refreshed based on customizable schedules.  Published data sources can also be organized by project and contain keyword tags to facilitate discovery.  These and other benefits make published data sources the optimal option for association analytics.
Data to Match the Business
The process of creating and editing data sources involves interacting with databases or other data formats.  Source data should be optimized for analysis and structured in a way that matches business processes.  A process to align data organization with actual business events and analysis goals such as Modelstorming ensures valuable business staff engagement and future flexibility.  Adding a new attribute involves simply adding it to a descriptive dimension table, while new dimensions can be quickly created and aligned with fact tables representing measured business events.  Likewise, new business events can be rapidly linked to existing descriptive dimension tables.
More Data to More People
Business staff throughout the organization can create and edit visualizations leveraging published data sources using a browser-based Web Edit feature that is part of Tableau Server and Tableau Online.  This feature provides an optimal set of capabilities similar to Tableau Desktop and does not require additional licenses.   These features include the ability to create any visualization type from the same data sources as Tableau Desktop.  In addition, custom edit and view permissions can specify which groups can access data sources and create visualizations.


The Analytic Workflow
In addition to rapidly creating data sources for exploration, visualizations and dashboards should align with a process for analytic thinking.  A common scenario involves business staff reviewing and interacting with higher-level dashboards to guide focus and spawn additional questions.  Traditionally, the analyst would then need to review individual reports to address an initial set of questions.  Dashboard and worksheet actions enable context-specific navigation and filtering which matches the data discovery process.  For example, a chart might trigger curiosity about a specific product category, such as “How are events including in this total distributed?  Did marketing campaigns contribute substantially to this total?  What are geographic patterns?”
A menu of potential dimensions can be available that guides exploration towards visualizations automatically filtered by the context of the bar chart value.  The result is ongoing questions and answers about the data.  The opportunities are limitless and help foster individual curiously and an analytic culture in your association.  The right implementation of these data exploration capabilities with the a data layer created specifically for the association will liberate the data and enable data-guided decisions for your association.

Association Analytics at Tableau Conference 2015

We had an amazing opportunity to attend the 8th annual Tableau Conference last week in Las Vegas.  For us, the highlight of the event was a great dinner where we celebrated our partnership with many of our association data rock stars.  We’re honored to have such amazing clients.   As we get back to the business of Association Analytics, we’d like to share some of the experience and knowledge from the conference.

Christian Chabot, the CEO and Co-founder of Tableau Software, opened the show and proudly described the growth of the conference which this year numbered over 10,000 participants.  He previewed the event and demonstrated Tableau’s commitment to the future and the mission of helping people see and understand data by noting that Tableau plans to invest more in R&D over the next two years than all the previous years combined.  Keeping with Tableau’s goal to empower people, the first event was “Developers on Stage” – the opportunity to learn about upcoming Tableau features directly from the development teams.

Developers on Stage TC15

The developers took the stage with enthusiasm rivaling the audience.
Individual development team lead demonstrated and described features that include:

  • Inclusion of multiple databases in a data source
  • Ability to “Union All” objects in a data source
  • Automatic clustering
  • Easy application of worksheet filters to dashboards
  • Outlier detection
  • Option to exclude table totals from color logic
  • Several additional international zip codes
  • Availability of additional external maps and GIS formats
  • Feature to highlight data based on text search
  • Version control in Tableau Server
  • Personalized Tableau Server home pages
  • Creation of “visualizations within visualizations”
  • Application of global formatting
  • Rapid optimization of visualizations for mobile devices

Factions of the crowd roared with approval as the developers announced their favorite features.  We eagerly signed up for the opportunity to beta test new product releases and continue to keep an eye on the future while understanding the product roadmap as a Tableau Partner.

Breakout Sessions & Hands-on Training

Most of the conference time was dedicated to extremely valuable breakout sessions and hands-on training.  Sessions tracks included Analytics, Big Ideas, Customer Session, Data Storytelling, Developer, IT, Workshops, and Zen Master Session.  I focused on targeted technical areas (some “Jedi level”) that are important to our clients which involve advanced analytics, optimal performance, R integration, and cloud-based architectures, while my colleague Bill Conforti focused on the key areas of analytics culture, adoption, and training which are so vital to association analytics success.
Guided Analytics: A Guiding Light in a Data Desert
This session demonstrated various advanced techniques to align Tableau with diverse analytic workflows such as dashboard interactions, actions between worksheets, and dynamically displaying visualizations based on parameters.
Jedi Strategies Using R-Integration
Tableau provides flexible R integration using script tasks that interact with a server (RServe) and behave similar to calculated fields.  The speaker led a demonstration based on a scenario from a great Tableau-focused blog and included accurately displaying flight paths incorporating the curvature of the earth.  Other great information included basic design patterns and ways to optimize performance.
Revenge of the Nerds: Advanced Analytics and Tableau
Tableau provides a range of advanced analytics capabilities leveraging diverse features.  Examples demonstrated included visualizations based on multiple plots, what-if analysis using stories, forecasting, trend lines, and level-of-detail aggregations.
Programming Tableau: Introduction to APIs
Tableau application programming interfaces (APIs) include a software development kit (SDK) for creating extracts, a JavaScript API for working with views in a browser, a REST API for managing Tableau Server, and JavaScript to develop web data connectors.  The session included demonstrations of examples of each type of API that associations can leverage to integrate with external systems such as conference registration providers and more efficiently create incremental data source extracts.
Turn Your Data Pile into a Data Stack with Tableau Online and Tableau Data Server
Tableau accommodates various architectures and data sources.  The speaker described cloud-based data sources such as Amazon Redshift and built an integration to the Twitter API using Google BigQuery as the intermediate data source.
Getting Your Performance Up
The speakers presented various opportunities to enhance Tableau performance and declared that replicating reports is the #1 reason for performance degradation.  We reviewed the Performance Recorder available within the Help menu along with resulting log files to identify performance bottlenecks.  The speakers listed several scenarios that negatively impact performance including custom queries, filters on table calculations, leverage show relevant values, blending data that can be available in a data source, and wide tables as opposed to tall tables.  They also noted that a good data warehouse can be better than an extract and Tableau visualizations are only as fast as the live underlying database.
Analyzing Data: The Balance of Art and Analysis
This session focused on creatively using features of Tableau to identify opportunities to develop analysis and presentations that business staff may not have considered.

Keynote Speakers

The keynote speakers were incredible and a great fit for the conference as data analytics using Tableau drives data-guided cultures, spawns creativity, provides deep analysis, and transforms work structures.
Daniel Pink, Best-selling author of Drive & host of the TV show “Crowd Control”
Similar to his fascinating books, Daniel Pink described characteristics that drive successful work cultures.  He discussed the key factors of autonomy, mastery, and purpose.  He concluded that people do great work when they are engaged, and self-direction is the key to engagement.  He also recommended carving out a few islands of autonomy and introduced the idea of the Autonomy Audit.
Neil DeGrasse Tyson, Astrophysicist & host of the TV show “Cosmos”
Dr. Tyson was a highly anticipated speaker and was predictably extremely entertaining.  He appropriately spoke on Back to the Future Day and evaluated the accuracy of science-themed fiction movies.  Although it is expected that such films take creative liberty, he stressed examples where filmmakers paid attention to other extreme details while neglecting science.  His main theme was the importance of data to identify objective truths.  Dr. Tyson even spent a considerable amount of time taking questions from the audience.
Hannah Fry, Mathematician, University College London Centre for Advanced Spatial Analysis
Dr. Fry provided very insightful observations about the analytics process including “numbers can’t speak for themselves, we need to speak for them” and “deeper analysis is needed to ensure what your conclusions are telling you”.  She presented scenarios that exemplify the value of data exploration and visualization where initial conclusions are made based on aggregated data.  For example, outliers influenced a popular study involving public debt driving significant policy decisions by skewing averages.  Dr. Fry also demonstrated revealing map visualizations involving London bike share and other data.


Sir Ken Robinson, Best-selling author, internationally acclaimed expert on creativity & innovation
The dry ironic sense of humor of Sir Ken Robinson was a great fit with the event and kept the audience very engaged as he provided fascinating observations about society, education, and innovation.  He described how traditional education conflicts with high life operates and is based on conformity and not diversity.  He noted that advancements in technology are driving an educational revolution as life is not linear, but organic.  His observations of the power of imagination, how imagination leads to creativity, and the importance of an environment to foster creative potential are very inspirational.  Sir Ken Robinson closed by referring to a Tableau customer testimonial quoted by Christian Chabot earlier in the event to the effect of “Tableau allows me to be creative, and I am not a creative person.”  He confidently noted that this is not correct – everyone has profound creativity in some way.
The Conference provided deep value event and we look forward to next year in Austin at TC16!

Powerful Visualization Choices (Part 3)

Previously we discussed the best use case scenarios for some common chart types: bar, line, and pie chart.  We also discussed some more advanced and less common chart types: maps and scatter plots. In this post, we are going to go over some more advanced chart types: histograms chart and bullet chart.
1. Histogram Chart
Like a bar chart, a histogram chart allows you to quickly compare information and see highs and lows. You will want to use a histogram when you want to see how your data is distributed across groups.
When to use:

  • To see how data is distributed across defined groups or “bins”

Make it shine:

  • Explore. Look for numerical measures that can be grouped to create dimensions. Try creating a variety of histograms to help you determine the most useful sets of data. You will want to make sure you create groups that are balanced in size and relevant for your analysis. Examples may include number of employees, age, years in the industry, etc.
  • Add a filter. Allow your audience to use filters to drill down into different categories and demographics to explore further.
Figure 1

Figure 1

Figure 1: Here we see sales figures grouped in $20 increments. You can quickly see that a majority of our sales are less than $20 and that we have very few sales that are over $520. Through the use of color, we can see that our profits are good for the $20-59 range, but that less than $20, where most of our sales are have a lower profit. If we had looked at each sale individually, it would have been more difficult to see these trends.
2. Bullet Chart
This chart type is excellent for showing progress against a goal. Essentially, a bullet chart is a variation of a bar chart, but with added features that allow the viewer to easily see progress against a goal. Unlike, dashboard gauges and thermometers, which are similar, the bullet chart can display key information and without taking up a lot of space.
When to use:

  • To compare a primary metric, like year-to-date revenue, to one or more other metric, like revenue budget or goal.

Make it shine:

  • Add shading or color. By adding color, such as red, yellow, green behind the primary measure, your viewer can quickly understand how performance compares to goals. Shading can also be helpful to give the view more context by showing a natural breakdown, such as quarters.
  • Include on a dashboard. When you combine bullet charts with other visualizations, the viewer is able to gain even more insight. You may want to include an association-wide metric and then also show a more granular breakdown.
Figure 2

Figure 2

Figure 2: On this dashboard, we see how year-to-date revenue compares to the revenue budget. In the chart on the left, you can see how each member type is going compared to their revenue budget. The grey shading indicates the quarterly budget. This is helpful as the year progresses to allow the viewer to see not only how the revenue is doing against the yearly goal, but also how revenue is tracking. The chart on the right is a summary of all member types and provides the same quarterly shading for quarter.

Planes, Trains, Automobiles… and Meetings

Each Labor Day weekend, analysts discuss the impact of gasoline prices and other factors on travel driven by an extra day off and the symbolic end of summer. Some estimates indicate that a greater number of travelers by car saved a collective $1.4 billion this year, much of which was spent elsewhere during
Deciding if and when to travel greater distances is a more complicated process since it often requires relatively expensive air travel with a commitment in advance. The price of airline tickets is significantly determined by the timing of purchase relative to travel. Analytics indicate that the optimal time to purchase tickets is generally between three and eight weeks prior to travel. The specific timing changes based on the time of year and also varies significantly by departure and arrival airports. It unfortunately does not require advanced analytics to observe that prices tend to rapidly increase beginning two weeks prior to travel.
Associations effectively create similar opportunities for customers through meetings and events. Associations spend considerable time and effort on planning and marketing activities based on a range of customer data including prior event participation, topical interests, individual engagement, meeting sessions, organization characteristics, continuing education requirements, and demographics. Registration patterns are closely monitored against prior year’s activity and current goals. Sometimes these patterns are not consistent with historical data. In some cases a trend of early registrants fails to continue and in other cases a late surge of registrants follows a period of marketing efforts.
Associations can supplement their AMS data with external sources to help explain such patterns. The U.S. Census Bureau makes very useful geographic data available including zip codes with latitude/longitude mapped to several other data points. The Census Bureau also offers an application programming interface to obtain detailed geographic data for specific addresses. This data can be used to calculate the distance between two points (it’s kind of a long story that involves the trigonometry I never thought I would use such as sine, cosine, and inverse tangent). Tableau data visualization software provides out-of-the-box geographic visualization capabilities based on data including zip code, area code, city, metropolitan/micropolitan statistical area, and even congressional district.
Various surveys and other analytics estimate that a common comfortable distance for car travel is around 200 miles.  Here is a map created using Tableau showing the population density by zip code within a 200 mile radius of Phoenix:
Here is a similar map based on the same color scale for Chicago:
A far greater number of individuals are likely to consider driving to a meeting in Chicago than a meeting in Phoenix. It is important to note that this straight line distance is clearly a rough estimate and encountering a large body of water such as Lake Michigan would challenge even the most dedicated meeting attendee. Fortunately you can leverage more advanced data sources such as the Google Maps API to estimate driving distances.
This data provides associations with great analytics opportunities to drive meeting participation by aligning with customer travel decisions. For example, marketing campaigns can consider travel decision timing and target specific airport markets. Registration pricing deadlines for individual events can incorporate location analytics. Your association can also create opportunities for strong customer engagement through efforts to help groups of potential meeting attendees organize buses together or even carpool.
Deriving travel distance analytics from customer location data is an example of gaining value from data. This demonstrates why it is important to consider analytics when designing business processes throughout the organization and not just as part of analysis after the fact. Increased meeting attendance often contributes to other benefits including member retention, publication revenue, engagement, and membership recruitment.
Understanding the impact of customer travel scenarios is a great way to leverage association analytics to create the future and grow your number of happy conference attendees.

Tableau Public for Associations

What is Tableau Public? It is a way for you to create visualizations and share them with the world for free.
Features and Benefits

  • Let’s start with the top feature. It is free! And as most college students can attest: cheap is good, free is better. For the low, low cost of $0, you will get 10 GB of storage.
  • Share with the world. When you save your data visualizations on Tableau Public, you will be able to send the link out to your community, and they will be able to see what you created without having to login. You can also embed your visualizations in your web site, at no extra charge.
  • Quick startup. All you need to do is download the Tableau Public app, create an account, and you will be ready to go. You can be off to the races in under 15 minutes.
  • Security on your data. New to Tableau Public, you can now configure, on a case by case basis, your visualizations to either allow the public to see and download your data or not.
  • Even if you are not using Tableau Public, the Tableau Public gallery will allow you to see and be inspired by what others have created.
  • You can create dashboards and stories, just like you could if you were using Tableau Desktop.

Open to the world

  • Open to the world. Although you can secure your data, once a visualization is published on Tableau Public, it is open to everyone. You need to be sure you are ready to open the kimono. The good news is there is no option to save data locally.
  • Storage is capped at 10GB, which if you have large data sources, means not much storage.
  • Data source limitations. You will not be able to connect directly to your SQL database or to Redshift, you are limited to Excel, Text, and Access files and odata. You will also not be able to automatically refresh your data.
  • Data set limitations. With Tableau Public you are limited to 10MM rows of data per workbook.

Tableau Public can be used to supplement your existing Tableau environment if you would like to share your visualizations with the public. It can also help your team evaluate Tableau and determine whether your association is ready for business intelligence. Hundreds of thousands of visualizations have already been shared on Tableau Public. Will yours be next?

Optimizing Your Association’s Dashboard Performance – Part 2

Last week we wrote about where and when to do calculations for your data visualizations in Optimizing Your Association’s Dashboard Performance – Part 1. In most scenarios we recommend that you perform those calculations within the ETL process. However, sometimes it is better to perform calculations within Tableau itself.  I am going to walk you through a couple of scenarios where the Tableau table calculations are used and how to create them.

Running Total

Example: Weeks Out Registration Report
This scenario will actually need a Tableau calculation as well as an ETL calculated field.  Prior to setting up this report, you will need to calculate how many weeks someone registered prior to the event.  This can be done with a quick date calculation such as “datediff(week, reg_registration_date, evt_start_date)”.  Once you have pulled the data into Tableau, create a simple line chart using the calculated Weeks Out field as your column and the count of records as your row.  From there, use the powerful Tableau Calculations tool.  With a running total calculation, you can see how your registration builds up as you approach an event. This calculation automatically updates as you choose different events or years.

Percent of Total

Example: Percent of Female and Male Members broken down by Ethnicity
A common calculation you can use is percent of total.  This calculation will allow you to determine what percent of your members are Male vs. Female and compare that by ethnicity.  This is a calculation that would be difficult to perform in your data mart.  Using a table calculation automatically calculates the percentages for your staff as they interact with your data visualizations.
Tabluau data calculations
Table calculations are a powerful tool, as they allow a flexible and detailed analysis of your data.  However, be sure to check that your data visualization performance is acceptable, otherwise an ETL calculation may still better serve your needs. The team at DSK is happy to confer with you regarding the optimal practices for creating calculated fields based on source data for your association.