Tuesdays with Tableau: Is your data ready?

By Gail Kluepfel

One reason today’s business intelligence applications are considered “self-service” is that business users can connect to a wide range of data sources with a few clicks – from Hadoop or SQL server, to text files, to the work horse of BI, Excel spreadsheets. Great! You no longer need a Computer Science degree to join together disparate data sources! However, regardless of your data source, self-service BI tools still assume that the data is in a consistent structure, and it is easy to spend a lot of time making it so.

Most self-service BI tools want data in a table like this:

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What do you do if your data source looks more like this?

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While the data source here is Excel, the structure is not a table with consistent data types and level of detail on every row. Some columns are only populated with data on certain rows, and some rows contain sub-totals. Within columns, values for customer names are combined with order numbers. 

One of my client’s only source of data was in this format, which wasn’t surprising since he was a top executive at a small company, and his outsourced accounting firm only provided him with nicely-formatted summary data each month. He wanted to use Tableau to analyze and trend data for the last several years, and was about to give up because he wanted to avoid manual cleanup of 30 or 40 individual spreadsheets from prior years. 

Thankfully, Tableau’s latest release (version 9.0) includes several new ways to automate your data preparation. For example, when you connect to an Excel spreadsheet that has multiple header rows, the Tableau Data Interpreter will detect the location and structure of the data and ensure it’s ready for analysis in the Tableau workspace. The new features also enable you to split data elements that are combined in a single column, and to pivot from multiple to single columns, or vice versa. For a complete list of data prep capabilities, check out the 9.0 features.

Still, there are cases where Tableau can’t help, such as auto-populating rows with data from a previous row. In this example, the column header “Customer Name” needs to be moved one column to the right, and the name of the customer needs to be populated down all the rows containing her Order IDs. 

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For this and even more robust cleanup, there are some great self-service data preparation tools that enable business users to create automated workflows to handle even the most gnarly data challenges. Alteryx in particular has an intuitive drag-and-drop interface. I recently downloaded the trial and, within an hour, set up several steps to crunch multiple Excel workbooks. Here is what the workflow looks like in Alteryx: 

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Each icon is a tool that you drag and drop onto the workflow surface and then click to connect. Once set up, you can schedule the flow to run at regular intervals, whereas previously you might have had to manually copy and paste data multiple ways and multiple times, or create macros and manually run them. With these and more data cleanup features baked into BI applications or add-on tools, self-service has never been easier. Check it out for yourself, by downloading the Alteryx trial. If you need a little guidance getting started, contact Marquis Leadership, and we’ll set you up for automated data cleanup success!

Tuesdays with Tableau: Tableau is Cool!

By Paul Ausserer

Photo by Joe Wolf / CC BY-ND

Last night, I had the fortunate opportunity to speak with the Management Information Systems (MIS) group at a local university, Western Washington University. The audience consisted of 20-30 juniors and seniors (most not old enough to drink) within the department of Decisions Sciences, many with a concentration in MIS. My goal was to sprinkle some “real-life” business experience on their academic plates by sharing my perspective on the technology and business opportunities surfacing today. It was me who left with some new perspective!

Shortly into my conversation, I asked the group, “What are some of the trending topics you hear about in BI (business intelligence)?” My inquiry was answered with silence. I’ll be honest, I’m not sure what I was expecting to hear. To get them thinking, I threw out some ideas: Big Data, Social Intelligence, Predictive Analytics. Heads started nodding. Bingo! I seized the moment to ask, “What are some of the prominent technologies used in BI today?”

Almost immediately, I heard, “Tableau,” and then again, “Tableau,” followed by another, and another. I was absolutely shocked (and delighted) that our future business leaders are not only familiar with, but immediately think of Tableau in the context of BI. By contrast, not a single other technology got any airtime. No PowerBI. No Business Objects. No Qlik. No Saas. Not even a single Excel. 

These are our future financial analysts, software engineers, accountants, business managers, and corporate executives. They are the Twitter, tablet, and Netflix generation. They’ve likely never seen a flip phone, read a real newspaper, or watched a show when it airs at 9/8 central. They will come into the business world with new paradigms and fresh perspectives, and they are excited about Tableau. To be fully transparent, Tableau headquarters is about 90 miles from WWU.

I came away from the discussion with the realization that Tableau undeniably resonates with this generation, which is no small feat in an age where the next big thing is just around the corner. Clearly, Tableau is that next big thing.

Five Questions to Ask About Your Team’s Stress Levels

By Mikaron Fortier-Gruenberg

Consider this: a company’s ability to attract (and keep) top talent and build a positive reputation around its brand depends on whether leadership actively makes space for managing stress levels. This is especially true during times of change, when people feel a loss of control or their commitment to the vision is taking a dip. Taking time for this kind of “mindcare” is crucial when intellectual property and knowledge-workers are the core of a company’s success.

How can a leader shift company culture toward mindfulness? Google appointed a Jolly Good Fellow to lead its Search in Yourself program, which uses the practices of mindfulness to train Emotional Intelligence skills, leading to resilience, positive mindset, and centered leadership. Aetna’s CEO brought in yoga practitioners to guide employees through meditative physical movement, which can greatly improve focus and creativity; studies show that regularly practicing yoga can increase the brain’s precious grey matter.

Here are five questions to help you weigh the readiness of your team to move toward mindfulness:

1. Do the people in your company, unit, or team take their allotted leave?

2. Has your team maintained productivity and met expectations? 

3. Are you and your team able to communicate new strategies and visions clearly?

4. Are behaviors such as perfectionism, control, and anxiety overcome in healthy amounts?

5. Do the people around you in your workplace make healthy choices (e.g. eat nutritious meals, pursue active lifestyles, sleep enough)?

If you answered “No” to any of these, then you may be ready for change. A good first step to enact change is to be a model for your team to follow. In the morning, take a moment to stop and consider your daily goals. Allow there to be one extra beat in your pause. Envision what you want to achieve before a phone call, a presentation, a team meeting. Gradually begin incorporating mindfulness into your conversations with your direct reports.

Change is always a challenge, but the good news is, you don’t have to go it alone. Marquis Leadership can offer you the tools and coaching you need to make this kind of cultural shift, and guide you through the process from beginning to end. If you are ready for a partner in stress management, we are here to help. 

Tuesdays with Tableau: 9 Reasons to Try Tableau 9

By Paul Ausserer

Tableau 9's new home screen makes getting started even easier!

The new Tableau 9 is packed full of game-changing enhancements that take the experience of data analysis to a whole new level. This is great news for leaders who want to get more out of their data without stretching timelines or budgets. To whet your appetite, here is a glimpse of my 9 favorite new features in Tableau 9:

1. Fast-Fast-Fast!

It’s not just a snazzy marketing campaign claiming that Tableau 9.0 is faster; this is the real deal. With combinations of the new data engine, parallel query processor, query fusion, and query caching, the user experience and application responsiveness are drastically improved. You won’t believe the night-and-day difference: open your 8.x workbooks in version 9 to see for yourself!

2. Hello, RegEx and Split!

I’ve always missed my long-lost string expressions from Tableau and am excited to finally see them in the core product. I used Split on my very first Tableau 9 workbook! Arming a data analyst with these powerful string manipulation methods makes Tableau a much better data cleansing, data preparation, and data analytical tool.

3. Level of Data (LOD) Expressions

LOD Expressions are a new syntax in Tableau 9 that both simplify and extend Tableau’s calculation language, making it possible to answer very specific questions using data aggregated at varying levels of detail. Gone are the days of wrangling the Partitioning and Addressing dialogs to align table calculations to meet your needs. Now, simply use a level of detail calculation to specifically identify the aggregation detail within the calculation itself, not within the visualization. This is a huge development – take some time to research and become familiar with LOD Expressions; you’ll soon wonder how you lived without them! (See Tableau’s whitepaper for more details.)

4. Web Calculation Editor

Were you just as disappointed as I when your Tableau Server client asked, “How do I create my own calculations”? The answer used to be, “Using Tableau Desktop.” With the new web calculation features, Tableau Server users can now create richer and more personalized analyses without a Tableau Desktop license. The gap between Desktop and Server is narrowing, and the capability for everyone to create business insight is growing!

5. New Analytics Pane

The one thing I have always loved about Tableau is its canvas-centric design and lack of nested ribbon menus or multi-level dialogs. With the new Analytics Pane, Tableau has made it even easier to stay within the visualization and the flow of analysis. Now you can drag a trend line or forecast directly onto a visualization without the need for a dialog. While this is a subtle change, this is proof that Tableau “gets it” when it comes to usability and staying focused on the data.

6. Calculation Editor

The calculation editor has improved on many fronts, but the best enhancement in my book is the introduction of intelligence for dimensions and measures. If you prefer to type your calculations, you can stay in the flow their work instead of grabbing your mouse and changing context. Mouse lovers get some love here as well – you can now drag and drop dimensions and measures to build your calculations. So, whether you prefer to type or use a mouse, Tableau has improved your calculation authoring experience!

7. Improved Map Search and Select

Have you ever wanted to zoom into a city or state directly and found yourself frustrated with the zoom controls? Well, with smart search on maps you can enter “Seattle” and the map will auto-zoom into that area. Another great enhancement is the radial and lasso selectors for much improved map interaction. You can quickly highlight all the data points surrounding a specific location in a radial fashion, or draw a custom area specific targeting your question.

8. Data Preparation

Tableau has added some data preparation features that make data manipulation much easier and keep you within Tableau (no more Excel!) For example, you can now properly shape rows of data that have separate columns for each Category or Year value into newly created rows of data. By pivoting the data you can now have Year as a dimension and work with your data in a much more intuitive manner.

9. Tableau Server Usability

The newly redesigned Tableau Server interface lets you view all workbooks on a single page, search across all content, and see breadcrumbs as you navigate. Spend less time looking for the menu options you want and more time understanding what your data has to say. Rebuilt from the ground up = Well done, Tableau!

The long story short is, you really can’t afford not to upgrade to Tableau 9. If you’d like to learn more about how Tableau 9 can help you reach your goals sooner, contact Marquis Leadership today. We would love to demo these new features for you, assist with your upgrade, and help you get where you’re going.

Tuesdays with Tableau: Tips and Tricks for Combining Data through Blending

By Gail Kluepfel
 
Last week I covered how Tableau enables you to combine data from different sources directly from your desktop interface. Tableau calls the technique data blending, in contrast with data joining, used to combine data from the same source when establishing the data connection. Today, I want to share some tips and tricks that aren’t obvious when blending data for the first time.

To create the blend in Tableau, you first create data connections for two or more sources. Once again, I’ll use the Orders and Returns tables from the Tableau Superstore data sample as examples of two different data sources. When you set a data source as Primary, you ensure that all rows from that source will be included in your view along with any rows in the Secondary source(s) that match on a common field; rows that don’t match in the Primary source won’t appear in the results.

There are two ways to set a data source as Primary – one is automatic, and the other is manual.

Tableau relies on subtle visual cues to indicate when a source is automatically set as Primary. Because these indicators aren’t immediately obvious in the UI, let me point them out here; not knowing which source is which could lead to unexpected results.

The Automatic Way

Here’s what you’ll see in the side bar of the worksheet view listed under Data after connecting to one or more data sources:

Two data sources (Orders and Returns)

As you can see, both icons are white. With a data source highlighted, click on a data element in the Dimensions or Measures windows, and the icon for that data source will show a checkmark in blue. Whichever data element you click and drag into your view first automatically becomes the Primary source.

Orders set as Primary

When you click a different data source, and select another data element, that source automatically becomes Secondary, and is indicated by a checkmark in orange:

Returns set as Secondary

Notice that there is also an orange link icon to the right of Order ID. Because this column has the same name as a column in the Primary data set, Tableau automatically creates a relationship between them, and “blends” the data sets through a left join from the primary to secondary table on the linked columns.

The Manual Way

The clearest way to see how Tableau is blending your data is to open the Relationships dialog box. In the top menu, select Data > Edit Relationships.

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Change which source is Primary or Secondary by selecting it from the drop-down menu. In this view, you can also add or remove columns to join the sources on, if the automatically-assigned ones aren’t sufficient.

Make Connections Active

After you have blending the sources using Relationships, be check that all of the columns you selected to join on are active in the data window for the Secondary data source. If the link icon is grey, then the join is inactive. Click on it to make it active.

The link icon will turn orange and a checkmark appears next to the Secondary source. Seeing “red” in this case is a good thing – it represents an active blend.

Adding More Data Sources

To add a third data source to the blend, use the same techniques. Here I’ve blended some Target data with the Orders data (Primary), using Month-Year of Order Date and Product Name to join the two sources, as seen in the Data > Edit Relationships box.

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Once blended, I can drag and drop data points from all three sources into my view, and even create calculated fields that use measures from one, two, or all three data sources. I can quickly see which products have had returned orders, the number of returns, and the sales amount for each, and whether or not there were targets associated with the products.

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I’m using some dimensions from the Order table, some from the Returns table, and measures from all three. As long as Primary and Secondary sources share at least one value in at least one column, you’ll be able to use dimensions or measures from any of the sources.

When deciding which source to make Primary, first decide from which data set you need all the records in your results, even if there isn’t a match in another data set. While Tableau’s data blending capabilities may not offer the same flexibility as custom joins in SQL, it certainly meets the needs for business users who want to pull together data sources quickly and easily.

Marquis Monday: The World’s Greatest Leaders

By Glen Stewart

What do US Supreme Court Chief Justice John Roberts, Jr., pop star Taylor Swift, religious figurehead Pope Francis, and Apple CEO Tim Cook have in common? They all made the top ten on Fortune magazine’s second annual list of The World’s 50 Greatest Leaders. Each of the 50 was chosen for his or her exceptional accomplishments as a leader over the past 12 months, and each can teach us a lesson or two about truly great leadership.

As Geoff Colvin states in his introduction to the list, the vetting team “set out to find singular leaders with vision who moved others to act.” They based their decisions on each nominee’s demonstrated effectiveness, commitment, and “courage to pioneer.” Let’s look at the top ten, in brief:

1. Tim Cook (CEO, Apple) filled the shoes of a legend and made changes in the world’s biggest company.

2. Mario Draghi (President, European Central Bank) made the list for performing a delicate international financial balancing act.

3. Xi Jinping (President, People’s Republic of China) received credit for literally changing the way business is done in China.

4. Pope Francis (Pontiff, Catholic Church) introduced change in an organization with global reach across multiple cultures.

5. Narendra Modi (Prime Minister, India) cleared away long-standing barriers to growth for businesses in his country.

6. Taylor Swift (Pop Icon) set a precedent for other young artists in the digital age and inspired girls around the world.

7. JoAnne Liu (International President, Médecins Sans Frontières) pulled together a scattered international band of volunteers to quell the Ebola outbreak.

8. John Roberts, Jr. (US Supreme Court Chief Justice) demonstrated that he can lead from the bench, with a track record of historic votes.

9. Mary Barra (CEO, General Motors) handled a highly visible crisis and embraced transparency to drive transformation.

10. Joshua Wong (Activist, Hong Kong Pro-Democracy Movement), spurred protesters to shut down Hong Kong, armed only with a smartphone and his convictions.

Each of these leaders shouldered massive responsibilities that required them to forge ahead with courage and dedication. They ultimately trusted themselves, understood what they value, and had a powerful impact on their organizations, the people they serve, and the lives they touch.

What qualities and characteristics do you share with the leaders on this list? How can you tap into your strengths to achieve your greatest results? If you could make changes for yourself or your organization, where would you start? Marquis Leadership is here to help you answer these questions. We’ll guide you through the process of identifying your greatest strengths and opportunities for change, and accelerate your ability to achieve what you want most.

Tuesdays with Tableau: Combining Data from Different Sources

By Gail Kluepfel

I think we can all agree, Tableau looks great in a demo with the sample data stored in Excel. But the true test of a self-service analytics tool is working with real data that may reside in more than a single Excel workbook. Thankfully, Tableau has two different methods of combining data to give the user flexibility: data joining and data blending. I want to address a few potential misunderstandings and highlight a few caveats to keep in mind when using either method.

Data Joining

When you want to work with multiple tables or views within a source (e.g., tables from the same database, sheets from an Excel workbook, text files within the same directory), Tableau works well when you join them. In most cases, performance will be much better than if you use blending. 

Using joins to combine data is easy to do and performs well in Tableau when the data resides in the same source. 

In Tableau, data joining is easy because you don’t need to know SQL. Simply drag and drop to integrate multiple tables and specify the columns to join on – choose the Data > Connect to Data menu option to get started. After connecting to the data source, drop a table onto the blank surface, followed by the table to be joined. Click on the set of interlocking circles which appears between the tables to open the Join window, where you select whether you want to use an inner, left, right, or full outer join. Then add the columns you want to join on. 

Learn about each join type in this excellent Tableau support resource.
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Creating joins at the data connection level is efficient: once you join data sources in a workbook, the final data source can easily be shared with Tableau Server, because data joining happens at the data connection level, not after a query is generated within a view. But even if two databases are on the same server, you won’t be able to join tables from each using this feature. For that, you’ll want data blending.

Data Blending

(Note: I won’t cover the basics of blending here; Tableau provides helpful resources to get you started.)

Two potential limitations: First, because data blending happens at time of query, after you’ve made data connections, performance can be slow, but in many cases this is still the best option. Second, you can’t blend two cubes.

Fortunately, you can blend a single cube with other data sources, and there are many other data sources that you can blend. To start, you can combine data from:

• two different databases (same or different servers),
• a database and an Excel file,
• a cube and a database or Excel file, or
• multiple files.

Primary vs. Secondary
Blending in Tableau requires you to designate one data source as Primary, the others as Secondary. You aren’t limited to two data sources – you can blend several – but only one can be Primary.

So what does the Primary designation mean? To those familiar with SQL queries, the primary source is like the “left” or first table in a left outer join. After blending, the results will include all rows in the Primary table but only those rows in the Secondary that match on at least one column you specify. If the Secondary source doesn’t have a match in the Primary source, it won’t be included in the results.

Say you want to blend sales amounts from orders in your CRM or ERP system with returns against each order stored in another system. Consider these two tables coming from different data sources: 

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Blend the Orders table with the Returns table, and the results will contain all orders for Xerox products but only include records from the Returns table with a matching Order ID (boxed in red), the only column these two tables have in common. This is expected “left join” behavior.

Tableau’s options for combining data are easy to use.

Joining and blending enable business users to query different data sources where they reside, rather than waiting for IT to replicate and centralize data through traditional development methods. While developers may not see Tableau as a robust dedicated integration tool like Microsoft’s SQL Server Integration Services or Alteryx, and technical analysts who use Excel’s Power Query may find Tableau less flexible, it does provide the easy-to-use graphical interfaces and high-performing capabilities that enable many business users to get the data they need. 

NEXT WEEK: Tips and tricks for working with Primary and Secondary data sources.