With more than 65 native connectors, Tableau is always working to bring data closer to our customers, while making it easier for IT to enable and manage data access. So, we are excited to announce that with Tableau 2019.2, we’ve upgraded our direct connection to Microsoft’s Azure SQL Data Warehouse to include support for Azure Active Directory (Azure AD) username and password authentication.
For larger enterprises with strict authentication requirements, this update will make data access management simpler. IT can now employ central ID management, using Azure AD for authentication with Azure SQL Data Warehouse.
Customers love Tableau’s partnership with Microsoft, as evidenced by Microsoft SQL Server being Tableau’s most commonly used data source. And as many companies are shifting to the cloud, customers can further leverage Tableau and Microsoft investments thanks to this new connector, first introduced with Tableau 2019.1.
Grow and scale with Azure SQL Data Warehouse and Tableau
Azure SQL Data Warehouse is a cloud-based enterprise data warehouse that takes advantage of massively parallel processing (MPP)—similar to the technology used by databases like Vertica and Teradata—which helps efficiently execute complex queries across petabytes of data.
As businesses grow, there is an increasing need to visualize and query every single piece of data, and Azure SQL Data Warehouse can help customers query hundreds of millions of rows at a lightning-fast rate. Prior to Tableau 2019.1, customers could connect to Azure SQL Data Warehouse through Tableau’s Microsoft SQL Server connector. This new connection offers customers a robust, finely-tuned connection to see and understand their data housed in Microsoft’s fully-managed cloud service.
The benefit Azure SQL Data Warehouse provides to customers is the ability to scale performance and resources independently through Microsoft’s Data Warehouse Units (DWUs). That means customers only pay for the computing resources they need, when they need them. Azure SQL Data Warehouse also stores data into relational tables with columnar storage, significantly reducing the data storage costs and improving query performance.
See Tableau and Azure SQL Data Warehouse in action
Here is a demo of Tableau against Azure SQL Data Warehouse. We’re exploring New York City Citibike data from 2018, analyzing hundreds of millions of individual trips. For this demo, we had Azure SQL Data Warehouse set to 500 DWUs—in the lower mid-range of the performance band.
Give the Azure SQL Data Warehouse connector a try, and let us know what you think.
Get started with Tableau and Azure today
The following tutorial can help you get your own Azure SQL Data Warehouse up and running: Azure SQL DW Tutorial. Please note: This tutorial only addresses local authentication.
If you are running your infrastructure and applications in Azure today, remember that Tableau Server is certified to run in Azure—you can run your entire BI and analytics platform seamlessly in the Azure cloud.
Our partnership with Informatica has always been a powerful and symbiotic one. Many of our customers rely on Informatica’s best-in-class data management solutions to connect, prepare, transform, and govern their data pipelines, enabling everyone to have access to trusted data when performing self-service analytics. Many Informatica customers choose Tableau to help make the most out of the data that they’ve integrated and cleansed, analyzing and transforming it to offer powerful insights that help drive the business forward.
With Tableau and Informatica together, our joint customers have been able to:
Easily integrate hundreds of cloud and hybrid data sources like Salesforce, Amazon Redshift, Microsoft Azure, Google Cloud, Snowflake, Workday, NetSuite, SAP, Oracle, Adobe, and Marketo, with data wizards, templates and prebuilt mappings.
Quickly transform and load data into a cloud data warehouse, such as Amazon Redshift, Microsoft Azure Data Warehouse, Snowflake, or into a Tableau data extract (TDE) file or Tableau Hyper format.
We are further strengthening this collaboration with a more powerful integration between Informatica Enterprise Data Catalog (EDC) and Tableau, announced today at Informatica’s annual user conference, Informatica World. Initially offered as a Google Chrome plug-in, the new dashboard extension more tightly and seamlessly integrates Informatica EDC within Tableau. Powered by AI, the Informatica EDC extension for Tableau provides a machine learning-based discovery engine that automatically scans data assets across the enterprise, catalogs them, and indexes those assets for enterprise-wide discovery.
“Enabling a culture of analytics requires a balance of self-service with governance so that everyone can trust and understand the data available for analysis,” our Chief Product Officer, Francois Ajenstat said. “Informatica’s new integration with Tableau brings the power of the Enterprise Data Catalog to end users in the flow of analysis. This will help people quickly discover relevant, curated data and empower them to uncover valuable insights and make data-driven decisions.”
Customers have been thrilled at the opportunity to combine Informatica’s deep cataloging capabilities within Tableau. This week at Informatica World, Illumina, a leader in genomics sequencing, described how it’s embarking on a customer experience transformation to enable analytics-driven decision-making. Illumina is using Informatica EDC to open up visibility of enterprise data and deliver consistent and trusted data to its users across the company. Coupled with Tableau’s robust, self-service analytics capabilities, Illumina employees of all skill levels are empowered by new insights to help provide proactive services that improve the customer experience.
See Informatica EDC and Tableau together in action
In this demo video, Associate Product Manager Blair Hutchinson is looking for sales information by state. He finds a dashboard that may provide insight into sales demographic data, but as it's not certified, he doesn't immediately trust it. Fortunately, the Informatica EDC dashboard extension provides him instant access to more information about the data, including its lineage and impact.
With a visual representation of how the data moves from the source to the dashboard, Blair validates the source of the data and has the confidence to move into further data exploration. He then uses Tableau's natural language interface, Ask Data, to type his questions to a published data source and receive rich visualizations that provide new insight.
Happy Certifiably Tableau Day! Today we’re sharing a little extra love and energy to celebrate those who have achieved a Tableau certification.
Reaching the top of a metaphorical mountain can elicit feelings of accomplishment or joy. You’ve pushed through feelings of doubt and uncertainty—do you know Tableau as well as you thought? Then finally, you can raise your hands to shout you’re Certifiably Tableau!
But passing an exam cannot be that exciting, you say? Some beg to differ.
Hearing how these emotions of pride and validation have taken different shapes to certified users demonstrates the diversity and commitment of the Tableau Community.
Some compare the feeling of getting certified to watching a favorite sports team triumph over their arch rival. Anil Pandita (Desktop Certified Associate & Desktop Certified Professional) remembers a particular 2009 Premier League match resulting in his team’s victory to finding out he passed his exam: “I recall that same moment of joy and excitement when I saw an email from Loyalist saying Congratulations for being a Tableau Certified Professional.”
The feeling can also manifest itself when others take the time to celebrate your accomplishments. Shiva Ram Chennapragada (Desktop Certified Associate) recalls a moment after becoming certified where the CEO at his company approached him and congratulated him for his hard work. Ritesh Bisht (Desktop Certified Associate) had another Tableau user dedicate his certification to him because of posts on LinkedIn about certification.
Becoming Certifiably Tableau can be a stepping stone in your work as well. It gave Virgina Moench (Desktop Certified Associate) the confidence to land her dream job using Tableau—which she starts in a few weeks! Vikram Gokhale (Desktop Specialist & Desktop Certified Associate) had the same kind of feeling: “I was glad about my certification the day I was selected for a substantially high-paying gig just due to my certifications.” Putting your certification titles and badges on your social profiles and digital resumes allows your skillset to speak for itself.
Becoming Certifiably Tableau is a verification of your skills that comes with permission to pause and reflect on your accomplishment. However, and whenever that feeling comes—we’re celebrating with you!
Have you been thinking about taking a certification exam or leveling up your certification? Now is the time to do it. We’re offering 10% off all online exams for one day only. Discount is automatically applied at checkout and you’ll have six months to complete the exam after the purchase. Sign up and get more discount details here.
The newest release of Tableau is here! This 2019.2 release includes exciting new ways to interact with your data and new dashboarding capabilities that come together to make a big difference for a more precise, streamlined authoring experience. Enjoy parameter actions, vector maps, and a new way to browse your content on Tableau Server and Online. Be sure to upgrade to the latest version of Tableau to take advantage of these new features!
Interactive analytics: Parameter actions and vector maps
Unleash your analytical creativity with parameter actions—the sky’s the limit with this simple, but powerful feature. With parameter actions, you now have the ability to visually change a parameter’s value. By interacting with marks on a viz, you can drive reference lines, calculations, filters, and even SQL queries, bringing visual interactivity to your data like never before.
Vector maps, new map styles, spatial calculations
We’re bringing a richer mapping experience to Tableau with vector-based maps. Vector-based maps look sharper and smoother as you pan, zoom in, and zoom out to explore your geospatial data. We’re also introducing brand-new map styles and layers. Bring more life and context to your data with Street, Satellite, and Outdoor styles, as well as building footprints, subway and train stations, and points-of-interest layers.
But there’s more—we’ve also brought spatial calculations to 2019.2. MakeLine support makes it easy to create two-point origin-destination maps, such as flight maps of airline routes, metro maps showing subway lines, and weather maps of storm paths. And with MakePoint, you can now turn latitude and longitude values from any data source (like text files or Excel) into spatial fields for use in spatial joins.
Redesigned content browsing experience: New homepage and left navigation
We’re also making it easier to find the content you care about on Tableau Server and Online. In 2019.2, we’re introducing a brand-new home page and fully redesigned navigation experience so you can get to your content faster than ever. Quickly access your favorited and recently-viewed dashboards in the new left navigation and discover new content through popular views to stay on top of what’s trending on your Tableau Server or Online site.
In addition to a new browsing experience, we’ve also added private custom views for the Viewer role on Tableau Server and Online. You can think of Custom Views as a way to bookmark your data—whether that be through filtering, sorting, or interacting to get to your preferred version of a dashboard. Today, Explorers and Creators can create Custom views, but based on feedback from customers, we’re happy to be extending this functionality to the Viewer role so that everyone can customize their views based on their goals.
New dashboarding capabilities: Custom reference line tooltips, show or hide dashboard containers, show or hide sort controls, and replace worksheets
We’ve heard your ideas in the community, and in this release we’re excited to deliver the following capabilities to make authoring dashboards easier, regardless of your skill set. Focus less on the mechanics of building dashboards and more on exploring and analyzing your data.
Custom reference line tooltips
You can now customize reference line tooltips—edit the tooltip text, or choose to disable the tooltip altogether.
Show or hide dashboard containers
We’ve added the ability to toggle between “visible” or “hidden” for any floating container on your dashboard. Elements that don’t need to be visible all the time, such as instructions, filters, or legends, can now be hidden to maximize screen real estate.
Show or hide sort controls
Authors can now preserve the sort order they’ve set on their worksheet by disabling the ability to one-click sort. Rest assured that end-users interact with data as you intended for the best dashboard experience.
Replace worksheets with a single click
And finally, get to that perfect dashboard faster with the ability to replace an existing worksheet in a dashboard with a new worksheet from the sheet list, with a single click. Dashboard spacing, dimensions, and aspect ratios all carry over for a faster, more precise authoring experience.
Ask Data updates: Conversational interactions, calculations, multiple sheets, and usage analytics
Ask Data continues to improve with significant updates in 2019.2, all to make it easier for you to ask sophisticated questions in a natural, ad-hoc way. You’ll notice a new interface allowing for more conversational interactions as you dig into your data. Replace a statement in an existing question by typing in your request. To change “average sales by state” to “average profit by state,” simply type “replace sales with profit.” You can also type things like “remove filter” to remove phrases from the query making it easier to iterate as you think of new questions. You can also now add calculations, such as the sum, difference, and ratio of two measures, on the fly. For example, type “Avg Sales/Avg Profit”, hit enter, and Ask Data automatically divides the measures for you.
Take advantage of the ability to create multiple worksheets in Ask Data—data to insight to dashboard, all without leaving the browser. Simply type to ask questions and iterate to create multiple useful visualizations and use them to build a fully functioning dashboard.
And finally, saving the best for last—2019.2 brings usage analytics to Ask Data. Data source owners and administrators can see what questions their users are asking and the most commonly-used fields in their data sources—all to optimize for the best possible experience. For example, you might see that a field labeled “Ttl_Sales” is a commonly used field. This gives you input to tune this field to be more accessible for your users. You could rename the field to a more readable name and check that the field has the correct data type or default aggregation.
Tableau Prep updates: New connectors, enhanced publishing experience
Accompanying the 2019.2 release is a brand new version of Tableau Prep Builder, 2019.2.1. In this release, we are introducing two brand new connectors: Amazon Athena and other JDBC! This means you can connect to and prepare an even more diverse set of data.
Also new in this release is an enhanced flow publishing experience. You’ve told us that it's often difficult to know or gain visibility into whether or not files stored in a network directory have been safelisted by your administrator. With this improvement, you can see the list of network directories that have been safelisted so you know the status of a directory right away.
Thank you, Tableau Community!
We can’t do this without you so thank you for your continued feedback and inspiration. Check out the Ideas forum in the community to see all of the features that have been incorporated thanks to your voices.
We’d also like to extend thanks to the many testers who tried out Tableau 2019.2 in beta. We appreciate your time and energy to help make this release successful.
When it comes to business intelligence, people have their routines. Some start their day by checking a critical business dashboard in their browser or using Tableau Mobile to direct their daily priorities, while others have a weekly analytics check-in to see how close they are to achieving their goals. To serve these different needs, people tend to filter and interact to get to their version of a dashboard—just the way they want it. If this sounds familiar, you could be saving time by creating one or multiple Custom Views on Tableau Server or Online.
Today, Explorers and Creators can create Custom Views, but based on feedback from customers, we're extending this functionality to the Viewer role in Tableau Server and Tableau Online 2019.2 so that everyone can customize their views based on their goals.
Our user community is incredibly important to us, and we listen carefully to feedback that we read in the Community Idea Forum. We’re thrilled to deliver on this frequently requested feature and enable people to see and understand data faster!
What is a Custom View?
A Custom View is a way to save the current state of a dashboard or view after you’ve made selections or changes like sorting, filtering, panning, zooming, drilling down, or altering parameters. Changes can be saved into scenarios, with each scenario being its own Custom View. You can easily save these scenarios as a default from the dialog menu so the interactions are reapplied automatically whenever you access this dashboard or view. Think of Custom Views as a way to bookmark your data.
Imagine, for example, that you’re the West Coast regional manager of a national store chain. You open the national sales dashboard every morning and you apply the same filters. First you filter State on Washington, Oregon, and California. Then you filter the Date field to include Q1 and Q2 2019. This shows your region’s year-to-date performance.
Since you’re the regional manager of the West Coast, you decide to create a Custom View with the State and Date filters. Every time you open the dashboard, you can quickly access a version with these changes. You can spend time digging into the data, not repeating the same operations day in and day out.
How to create Custom Views
When you have a dashboard exactly as you want it, with all the filters, sorts, selections and zooms applied, click the View option in the toolbar. Enter a name for your Custom View that helps you remember what interactions it has. Then click Save to preserve the Custom View.
As an option before saving, you can ‘Make it my default’, which means that, for you, any link that points to this dashboard’s original view will automatically include your modifications. One major reason you might want to do this is so that one of your favorites always points to your Custom View, rather than the original version.
Let’s suppose you crafted a perfect modified dashboard, but want to get back to the original or a different view. Click the View action in the toolbar to bring up a list of all the different Custom Views you’ve created, listed under My Views. The original view and public Custom Views created by others with an Explorer or Creator license appear under Other Views.
Share or Subscribe using Custom Views
Now that you have your Custom View, you share the link with others who have access to the dashboard or have it automatically sent to your email at a regular schedule. Share and Subscribe options work seamlessly with Custom Views. Access these options from the viz toolbar.
Try Custom Views today
Custom Views are a great way to quickly compare different scenarios, save time from reapplying interactions, and get customized subscriptions. Download the newest release and learn more about all the new capabilities in the Tableau 2019.2.
Editor's Note: Visual Risk IQ is a long-standing Tableau Partner that specializes in helping finance and internal audit professionals see and understand their data. The firm has completed hundreds of successful data analytics projects for clients in all industries and their innovative approach to on-the-job training and mentoring helps shorten the time to insight.
Background: Data analytics is not “new”
Data analytics within the finance, risk and internal audit worlds are far from new. Spreadsheets became pervasive in finance and audit more than 30 years ago and traditional scripting languages and report writers are equally “of age” in the business world. Despite these advances in technology, most internal audit programs still begin with key steps that say “select a sample of transactions.”
Professional standards have mandated for more than 10 years that internal auditors consider the use of data analytics during planning, yet we find in practice that sampling is the predominant testing method for many internal audit teams. Even when entire populations of data are evaluated, they are tested as often with spreadsheets as they are with more robust tools. Spreadsheet use can create potential blind spots for auditors, particularly around data integrity.
In this blog, we'll share with you how to improve query design and create time savings by automating recurring risk and audit steps and solving for blind spots spreadsheet use can cause. We begin by describing the skills that effective audit teams need to execute on these process changes. Read on to learn why it's necessary to incorporate data analytics—at the minimum, data-driven alerts—instead of only sampling or spreadsheet analysis into your audit and risk functions.
In our experience, a repeatable process for audit and risk-focused analytics requires changes in approach that incorporate connecting business questions with an understanding of underlying data sources. At Visual Risk IQ, we developed a QuickStart process brings business and data-focused professionals together to connect their business questions to data sources.
What skills are needed for data analytics?
The single biggest key to success is ensuring that finance and audit domain expertise is supported by team members who have equally strong knowledge in data acquisition and data preparation. It definitely takes both of these skills for success with self-service data analytics. Having completed over 200 successful, data-driven internal audit projects across a variety of industries, we Visual Risk IQ continually see that this combination of skills is required.
Borrowing from the Association of Professional Research Analysts, who have developed a Body of Knowledge specific for data analytics in the fund-raising world, we have found that similar areas of expertise are needed for successful data analytics for finance and audit professionals:
Data acquisition and manipulation
Visual reporting techniques
Finance and audit domain expertise
Change management and strategic thinking
All of the above skills are rarely if ever found in the same individual, hence we believe that finance and audit-focused data analytics should definitely be considered a team sport instead of an individual one. And that supplementing audit or finance skills with data-specific and visual reporting schools is an especially powerful idea.
In our experience, the visual reporting techniques are often the least developed skills from this Body of Knowledge in the finance and internal audit community. Finance professionals are very quick to run confirmatory queries to identify issues; for example, confirming if any invoices have been dated prior to a purchase order date. But instead of first exploring the number of days between invoices and purchase orders to understand the average or a minimum or maximum number of days, a confirmatory table that says “list all if Date A is prior to Date B” is too often considered an ultimate answer. Perhaps finance and audit professionals are better with confirmatory queries because scripting languages and traditional report writers are better tools for developing confirmatory queries than they are for developing exploratory queries.
Exploratory queries lead to data discovery and aligns better with the future of self-service, data analytics. Special IT or programming skills are no longer needed because modern tools like Tableau make exploring and analyzing populations of data easier. It only takes a few clicks to rank or sort transactions from largest to smallest or oldest to newest. And together with a few filters, an interactive dashboard can be created for exploration and finding greater insights than ever possible with spreadsheets or scripting languages.
For more on visual reporting techniques including matching your chart type to your business question, we recommend Stephen Few’s Show me the Numbers book and blog. One of the most important techniques for visual reporting done with Tableau are dashboard actions and “viz within a viz” where a high-level exploratory chart (e.g., time series or part-to-whole) can be used to select or filter a Ranking chart specific to a category or date range. This allows the person who is asking and answering an initial question to solve their next question without additional programming.
Other auditing tools and their limitations
While spreadsheets can be versatile and most auditors and analysts are highly experienced with them, we find that spreadsheet use creates potential blind spots for those seeking a full picture of their data, particularly around data integrity. The risks of spreadsheet formula errors and even accidental updates to data while scrolling in, sorting, or filtering a file is too great to make spreadsheets a trustworthy choice for most internal audit use. You may miss outliers and patterns from exploring entire data populations with ordinary exception queries or working with limited data sets in spreadsheets. Beyond using a more robust analytics platform that supports querying all of your data, your team needs to be staffed appropriately to manage evolving risk and audit functions.
Even for organizations that occasionally use scripting languages in their internal audit work, it is common for the tools to be used only once or twice and then atrophy with staffing changes. Perceptions and even realities regarding the high costs of ad hoc analyses cause these scripting tools to become “shelfware” at many organizations. We advocate that data analytics and particularly exploratory, visual analytics should be a more regular and repeatable process within internal audit planning, fieldwork, and reporting.
Great examples of visualizations for better auditing
Our favorite visual reporting applications allow for exploratory querying, which leads to data discovery, supporting a self-service, data analytics model. Examples we like for finance and audit professionals include travel and entertainment testing or Procurement Cards, since error rates are often high due to after-the-fact approval for this sort of spending.
This dashboard for Oklahoma P-card data can quickly show outliers indicating duplicate or out-of-policy expenses. This visualization is one of our favorite exploratory queries.
More recently we’ve used Tableau to identify groups of disbursements that may have implications for ASC 842 (a new Standard on Accounting for Leases). The white space in each vendor payment row in the Gantt chart below shows the time between payments of similar amounts. Regularly-spaced groups of vertical lines indicate an increased likelihood that these payments represent a lease requiring disclosure under this new accounting standard.
What visualizations have you created that have made an impact on your finance and internal audit teams? For more inspiration, consider joining the Tableau Office of Finance community user group and attend meetings to interact with and learn from your peers.
Recently, Tableau introduced a faster way to mobilize your dashboards to users on their phone with the automatic mobile layouts feature. Now every new dashboard includes a mobile layout. Besides automatically appearing, the new smart technology builds with you, so feel free to focus on the desktop while it works behind you. As long as the setting is set to automatic, it continuously updates everything you add, remove, or change on the dashboard.
Tableau’s smart layout follows known best practices, reading from left to right to help our dashboards flow nicely on the phone. Each object on our dashboard will build down for mobile. If I keep this in mind while I design, I can make my transition from desktop to phone quite smooth.
In this post, I put automatic layouts to the test with a dashboard analyzing shipping from the superstore data set that comes with Tableau. I’ll review some best practices for creating mobile dashboards and explain how this relates to the new automatic layouts feature.
I designed this dashboard using floating objects and made use of set actions. Will automatic layouts preserve the simple elegance of this dashboard?
Start building dashboards with mobile in mind
One principle for successful mobile dashboards comes from the basics of web design. Web pages use CSS to create breakpoints. I don’t want to use CSS, but I do want to find ways to tell Tableau what I want. Sometimes, we might build these KPIs as a whole unit or in numerous pieces. I know that I want to make a 2x2 box on my phone layout, both to make the best use of space and to create something that feels natural on the phone. With this in mind, I’ll build my chart that way from the beginning.
I’ll also consider some good design practices for mobile, like surfacing the high-level takeaways for the audience, with intentional interactivity. Remember that your audience won’t always be able to drill down on a small screen, so you have to think about giving them the most important metrics and KPIs that they need to have readily available to them.
Minimize glare and make clicking easy
Fight the blue light: Screens are probably one of the key offenders in the blue light war. It used to be the sun. With always-on set-to-the-max-brightness screens that are near-constant, we’re setting our retinas up to fail. White in particular loves to amplify this effect, which is why some of the nicer phones offer a night-mode and blue light filter. To ease screen glare, I’ve opted to soften the white with a lemon cream background.
Make vizzes easier to click: Smaller screens not only mean less real estate, but reconsidering the how the data itself is presented due to an entirely different shape (most people interact with their phone upright). We also have less precision on a phone. We’ve learned (and anyone who remembers the 1980’s or ’90’s knows it was learned) to use mice as inputs. Our fingers are instinctual, but the lack of texture and minimal feedback is not. With this is mind, I made the bars in super chunky to help my users click.
Intentional filters: Phones have a compressed space and are likely used in the middle of other activities. My targeted end user may be in a warehouse and dividing attention. I’ve also added a set action focused on the Shipping Mode that activates the charts surrounding it. This highlights that category and lets me compare it to others versus removing details with a traditional filter.
Use automatic layouts for instant mobile-friendly dashboards
Now I’ll bring this dashboard into the device designer to create the mobile version. Right away my dashboard looks like this:
In the image above, you’ll notice that I have new options in my dashboard pane. Automatic layout is selected and my dashboard is slightly greyed out as a signal that I don’t need to do anything. Tableau Desktop tiles each chart one by one in z-reading order. I don’t need to, but I could choose to edit this if I want to tweak it even further. This dashboard looks exactly how I hoped it would! If I leave it automatic, it will continue to update as I make changes.
My tips for optimizing automatic layouts:
● Filters go above the charts that display them. Using a global filter? Select them from the first chart, so it goes to the top of the dashboard.
● Automatic follows a z-reading pattern based on the upper left corner of every worksheet. Remember this when creating the desktop version of your dashboard so you have an idea of how it will display on mobile.
● Floating designs get converted to tiled in the mobile layout. Items that are stacked get read by their starting pixel.
Learn more about creating automatic phone layouts in Tableau.
Self-service data prep is an extension of the same paradigm as self-service analytics: allowing people to answer their own questions with data that was previously inaccessible. Adding additional data sources helps answer further questions and allows the data worker to provide more context to the consumers of their analyses. You can greatly reduce your analysis time when you can produce the datasets yourself. You can also more easily validate data sets to be sure that you are accurately reflecting reality. Everyone wins!
This is a lesson we’ve learned with the launch of Tableau Prep Builder and now with our Preppin’ Data project — a weekly project designed to get people hands-on with data preparation. Each week a set of data is released along with a series of requirements and end-goal of how the data needs to be prepared. During the week, participants share and discuss their ways of tackling the problem and the following week, a possible solution is released. These projects explore various facets of data preparation and aim to not only provide realistic examples of data preparation problems, but also keep participants on the cutting edge of Tableau Prep Builder releases by highlighting new or interesting features.
Let’s dive into why self-service data prep is important for individual analysts and organizations, along with some further lessons learned from our time with Preppin’ Data.
The importance of self-service data prep
Data is everywhere but to make use of it as analysts we first need to gather, structure, and clean the data. Traditionally, this was formally done within databases by IT teams within organizations, but also informally within Excel workbooks. The formal “wrangling” of data to complete analyses involved writing SQL code within the database itself. Most business users and business-side analysts simply didn’t know how to write SQL. Those that could, simply didn’t have the access or permission within the database to write the queries.
For the informal data files, wrangling the data involved a lot of copying and pasting or deleting rows and columns. The informal wrangling burned hours of people’s time on an uninspiring task that would just have to be repeated again the next day, week, or month. Data was hard to source and hard to load into the tools that business users and analysts were already using to answer questions. This challenge is not limited to business data. It was also compounded by data sources now living on the internet, behind APIs, on PDFs, and more. This is why self-service data prep is so important.
How to get started with data prep
1. Understand the basics of data prep
There are a few main tenets of data preparation. These include cleaning the data, restructuring the data, combining data together, and validating the data. These tasks are achieved through various means such as removing unnecessary data, using formulas and calculations to get new data or modify existing data, and merging different data sets together through joins and unions.
2. Understand how self-service data prep can shape and improve your analysis
Self-service data preparation helps prevent you from being restricted to the data that you’ve been provided. The ability to restructure and combine data to suit your specific needs can reveal insights that were hidden or difficult to discover. It can speed up ongoing analysis by pre-formatting your data so less time is wasted on aggregating, calculating, and comprehending. It allows you to be more confident in your analysis by ensuring the validity of the data yourself and providing a deeper understanding of the values in your data and how these values link together.
A great starting point for understanding the basics of data prep and how it can help your analysis, as well as how Tableau Prep builder fits into these processes, is this short whitepaper on data preparation best practices.
3. Practice with public data sets: The Preppin’ Data project
So how do you start learning and applying self-service data prep? That’s what we sought out to solve with the Preppin’ Data project as we were conscious that not everyone has had exposure to this type of work. Preppin’ Data is designed to empower the new ‘self-service data prepper’ to gain experience dealing with the most common challenges that they are likely to encounter in their day-to-day work. Let’s face it, data work is all about accuracy. If you make mistakes, your analysis (and future analysis) will likely be ignored, rendering the work useless. Learning how to prepare data sets correctly becomes a fundamental building block for great data analysis. But data prep is still a skill that needs to be practiced. This is why we have found that Preppin’ Data has lots of experienced users joining in alongside the ‘newbies’ too. Everyone needs to practice this skill.
What we’ve learned from the Preppin’ Data project
Preppin’ Data wasn’t just for the people participating in the challenges. It was also for the ‘Dr Preppers’ (Jonathan and Carl) as the initiative started with a conversation over a coffee machine at the Data School where it quickly became apparent that others would benefit too. Jonathan, a new Data School consultant, questioned Carl, the ‘Other Head Coach’ at the Data School UK, as to the best way to start getting more hands-on practice with Tableau Prep Builder. Simply put, apart from a few great blog posts, there were limited opportunities to regularly practice using Prep Builder or work across a wide range of different industries’ challenges. Preppin’ Data is a weekly challenge that is posted on a Wednesday and the solution post shared on the following Tuesday. The challenges have taught both Jonathan and Carl more than they originally thought (by a long way).
Participants submit their thoughts, questions, and solutions (solely pictures of flows for the time being) on Twitter and via the Preppin’ Data site. This has caused a lot of unintended benefits:
Learning how to document a Tableau Prep flow in the best way:
Use the step renaming and descriptions.
Use the ability to change the colour of the steps to make the data steps feel like they are actually mixing (obviously a blue and yellow data flow when joined makes green).
By using the product more, we have found that Preppin’ Data has uncovered a few unknown bugs. This is great as the Tableau team are quick to make the amendments to fix the identified issues.
Building a Tableau Prep community:
As people discuss their work with Tableau Prep more and more, solutions are shared and best practices are formed.
Some people complete Preppin’ Data challenges in other tools such as R, Python, SQL, and Alteryx as people explore what is the best tool for the job. This conversation helps us learn how to teach Tableau Prep Builder to people who currently use other tools.
Tableau Prep Builder has lowered the barrier to entry for a lot of people who have never had the chance to self-service their data prep needs. The common aesthetic, calculation syntax, and user focus has enabled a lot more people to get hands-on with data prep like never before. Preppin’ Data will continue (as long as it keeps being useful) to give more examples to allow people to make a start with preparing data and work with Prep Builder in a safe space.
Submit images of your flow on Twitter and discuss your techniques with others by using the #PreppinData hashtag. There is never one correct way and this has been a really important lesson for the 100+ participants we have had to date. The feedback between participants has started to form a Prep Builder community that is still in its fledgling state. We want you all to come and take part in it to help it flourish and create even more learning opportunities.
We’re back with Best of the Web—a roundup of some of the best Tableau blogs on the world wide web. Due to some administrative errors (ahem: “Andy didn’t send emails”), we missed a whole bunch of superb posts from the last few months, but don’t worry, we’re making up for it by posting even more resources this month. And this month’s content is chock-full of inspiration.
To start, Zen Master Bridget Cogley looks at the meaning of “data literacy” from the perspective of a linguist. Bridget provides an overview of the term literacy and then applies it to data.
Finally, if you thought Set Actions were powerful, wait until you see Parameter Actions in the Tableau 2019.2 release. This new feature is, I predict, going to create another explosion of creativity among the community. I can’t wait to see what ideas you come up with. Some of you are already out of the blocks with ideas, and I want to highlight Josh Milligan’s implementation of Parameter Actions to create Minesweeper in Tableau. You could argue that it might not be analytically valuable, but it’s Minesweeper...in Tableau...and it’s amazing!
We already know that marketers can make better decisions, act with confidence, and demonstrate their impact when they are data-driven. But data can play yet another role in marketing departments: developing content.
With an estimated 3 million blog posts published each day, content teams need ideas that will help them stand out. Data can help your organization tell stories that no one else can. Using your company’s own data, you can generate truly unique, audience-ready insights. Or you can combine public data sets with your organization’s distinctive voice and values. The result? Original content that attracts eyeballs and starts a conversation with your audience— all while remaining authentic to your brand.
Content teams from organizations around the world are using Tableau Public to publish and share their data stories. To inspire your next great data story, we’ve rounded up some of our favorite examples of Tableau Public vizzes used for content marketing.
Put your company data to work
Believe it or not, you already have a wealth of unique data just waiting to be shared! Partner across your organization to uncover data sets, then determine what stories would be interesting and valuable for your audience.
Get more mileage out of your customer data
Spotify is a master of reusing their customer data, regularly transforming their listening habits and behaviors into powerful, timely stories. In their coverage of Pride, Spotify’s data scientists analyzed over half a million playlists labeled “Pride” or “LGBTQ.” They used their findings to show which artists were most popular in each U.S. state.
Show off your survey data
Visualizing survey data can help your organization get the bigger picture— why not share that picture with your audience? It will come as no surprise that we love incorporating data into our content marketing at Tableau. Here’s an example of how we transformed survey data into a story our audience loved. Each year, we announce the business intelligence trends we believe will gain momentum in the industry. We also surveyed our community, asking them to vote on the relevancy of each trend and to select the eleventh trend. We visualized the results of this survey in our report.
Build stories around external data
You’ve discussed using proprietary data in your latest content brainstorm. Still coming up short? Luckily, there’s plenty of publicly-available data out there— use it to tell compelling stories that reflect back on your organization.
Position yourself as an industry thought leader
Is your content team tasked with creating thought leadership content? Try visualizing leading trends or poignant topics in your industry. There’s plenty of publically available data that you can leverage for these projects. For example, EY used data published by the UK Government to create a series of dashboards. These dashboards help their audience explore the UK gender pay gap—a distinctive and valuable experience that also gives EY an authoritative voice on gender pay gap reporting.
Help your audience answer questions
The right data in the right context can help your audience answer their most pressing questions. Consider this example from U.S. real estate brokerage Redfin. In recent years, people all over the U.S. have become increasingly worried about losing their homes to wildfires. To answer questions about their risk, Redfin visualized public data about wildfires. Published as part of a larger blog post, the interactive viz let anyone learn about their county’s risk.