Qlik Luminary Life Joe Warbington Vizlib header

Post: Qlik Luminary Life – Joe Warbington of Vizlib

Here at Motio we’ve started a new blog and video interview series entitled Qlik Luminary Life. The purpose of this series is to highlight and showcase Qlik Luminaries, find out why they love Qlik and get to know them on a more personal level.

For our first interview, we had the opportunity to speak with Joe Warbington, Senior Director of Industry Solutions at Vizlib and learn more about the challenges Qlik has helped him overcome, his hobbies, and his extensive knowledge of Wu-Tang Clan songs that he memorized for a Qlik app.

Why did you decide to apply to be a Qlik Luminary? 

For years, while I was at Qlik on the healthcare team, I admired and made a number of great connections with the Qlik Luminaries. It was my mission to someday join the party.

Favorite thing about Qlik? 

You might expect me to say the visuals or the APIs, but hands down my favorite thing about the Qlik technology is the power of the grey. It is mindblowing for people once they can understand that in most businesses and for many uses, it’s the data that’s missing that might be more important than the data that’s present and visualized. In healthcare, it was so powerful to help organizations see which medications weren’t prescribed, which diseases and conditions weren’t co-indicated, and most importantly what patients hadn’t been seen yet. That’s how things improve: the missing data – the stuff in the grey – are the opportunities.

Tell me about the biggest challenge Qlik helped you to overcome. 

That’s tough, as I’ve seen a lot of great Qlik apps and solutions over the years, many of which in healthcare had a direct impact on the lives of patients. Maybe one of my favorites and one that I keep coming back to improve and refresh is an app around my health data. For years, I’ve been tracking my fitness passively through my iPhone. When I later got an Apple Watch, I started tracking my heart rate and workouts as well. It’s mounds of data, on just me. Exporting the file from Apple Health via the APIs results in gigabytes of XML data that I massage and bring into a comprehensive Qlik app. I can easily see how my health metrics are affected by my lifestyle choices, workouts, travel, weather, etc. I’ve even used to show my doctor about my health because it was way more data on me than my healthcare providers have. I wrote about it here https://blog.qlik.com/the-electronic-sickness-record and here https://branch-blog.qlik.com/apple-healthkit-a-delicious-qlik-recipe-d61167e7ab89. A shining moment with that app? I got to demo it to executives from Apple during a large healthcare IT conference last year – they loved the functionality and of course the visual branding.

Advice for those wanting to become a future Luminary? 

Get social! The existing community is active in a number of channels and loves to be helpful and will share your work. If your use of Qlik is mainly related to your job and you can’t share that, start building apps using public data. Kaggle is a great resource for a variety of data sets.

Tell us a little bit about what Vizlib does. 

Vizlib is Qlik’s leading technology partner for value-added products. We help make Qlik Sense shine with new visualizations, increased capabilities, and amazing customization options that help make your data talk. If you can think it, you can build it with Vizlib + Qlik Sense.

When you’re not working and being a Luminary what hobbies or activities do you enjoy?

Like many folks, it’s tough to stop thinking about data and visualizations. But in my spare time, I love playing with and making my son laugh, and training capoeira – a Brazilian martial art.

Name a song you have completely memorized.

Besides Elmo’s World theme song (see above about my young son)? I studied a lot of Wu-Tang Clan songs for a rap lyrics project. Yep – a Qlik app. It analyzed the largest vocabularies of famous rappers.

What would be your first question after waking up from being cryogenically frozen for 100 years? 

Where’s the closest coffee shop?

Interested in learning more about Joe Warbington? Be sure to follow him on his social media handles listed below and be sure to stay tuned for episode two where we get to know Nitesh Sethi, CEO of Cliqvenus.

If you’re a Qlik Luminary and are interested in being featured for our blog series contact Michael Daughters at mdaughters@motio.com.

Scroll to Top
As the BI space evolves, organizations must take into account the bottom line of amassing analytics assets.
The more assets you have, the greater the cost to your business. There are the hard costs of keeping redundant assets, i.e., cloud or server capacity. Accumulating multiple versions of the same visualization not only takes up space, but BI vendors are moving to capacity pricing. Companies now pay more if you have more dashboards, apps, and reports. Earlier, we spoke about dependencies. Keeping redundant assets increases the number of dependencies and therefore the complexity. This comes with a price tag.
The implications of asset failures differ, and the business’s repercussions can be minimal or drastic.
Different industries have distinct regulatory requirements to meet. The impact may be minimal if a report for an end-of-year close has a mislabeled column that the sales or marketing department uses, On the other hand, if a healthcare or financial report does not meet the needs of a HIPPA or SOX compliance report, the company and its C-level suite may face severe penalties and reputational damage. Another example is a report that is shared externally. During an update of the report specs, the low-level security was incorrectly applied, which caused people to have access to personal information.
The complexity of assets influences their likelihood of encountering issues.
The last thing a business wants is for a report or app to fail at a crucial moment. If you know the report is complex and has a lot of dependencies, then the probability of failure caused by IT changes is high. That means a change request should be taken into account. Dependency graphs become important. If it is a straightforward sales report that tells notes by salesperson by account, any changes made do not have the same impact on the report, even if it fails. BI operations should treat these reports differently during change.
Not all reports and dashboards fail the same; some reports may lag, definitions might change, or data accuracy and relevance could wane. Understanding these variations aids in better risk anticipation.

Marketing uses several reports for its campaigns – standard analytic assets often delivered through marketing tools. Finance has very complex reports converted from Excel to BI tools while incorporating different consolidation rules. The marketing reports have a different failure mode than the financial reports. They, therefore, need to be managed differently.

It’s time for the company’s monthly business review. The marketing department proceeds to report on leads acquired per salesperson. Unfortunately, half the team has left the organization, and the data fails to load accurately. While this is an inconvenience for the marketing group, it isn’t detrimental to the business. However, a failure in financial reporting for a human resource consulting firm with 1000s contractors that contains critical and complex calculations about sickness, fees, hours, etc, has major implications and needs to be managed differently.

Acknowledging that assets transition through distinct phases allows for effective management decisions at each stage. As new visualizations are released, the information leads to broad use and adoption.
Think back to the start of the pandemic. COVID dashboards were quickly put together and released to the business, showing pertinent information: how the virus spreads, demographics affected the business and risks, etc. At the time, it was relevant and served its purpose. As we moved past the pandemic, COVID-specific information became obsolete, and reporting is integrated into regular HR reporting.
Reports and dashboards are crafted to deliver valuable insights for stakeholders. Over time, though, the worth of assets changes.
When a company opens its first store in a certain area, there are many elements it needs to understand – other stores in the area, traffic patterns, pricing of products, what products to sell, etc. Once the store is operational for some time, specifics are not as important, and it can adopt the standard reporting. The tailor-made analytic assets become irrelevant and no longer add value to the store manager.