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Post: Qlik Luminary Life Episode 4 – Juraj Mišina of EMARK Analytics

Episode 4 of Qlik Luminary Life is here! This week we had the opportunity to interview Juraj Mišina to learn more about what it’s like being a Senior BI Specialist at EMARK, one of the largest Qlik-exclusive consultancies in Central Europe, as well as a hobby beekeeper and father.

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

An honest answer probably is to challenge myself. I just wanted to see if I can manage to join this group of distinguished Qlik enthusiasts. It also gives me a bunch of nice perks, like an opportunity to network with some of the brightest Qlik minds in the World and get exclusive information about product development. You just don’t want to miss out on this.

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

The biggest challenge is always the most essential one: data quality. Thanks to the flexibility and agile nature of development in Qlik, we are able to quickly recognize problems with source data and fix it. Probably the second challenge would be ever-changing customer requirements. The speed in which you can answer to “Err, that’s not exactly what I expected” is just extraordinary.

Advice for those wanting to become a future Luminary?

The mission of Qlik Luminaries is to be advocates. But being an advocate does not mean to be a blind promoter. Yes, promote Qlik (there’s so much to promote!), but challenge it as well. Qlik loves to hear feedback, and while some of our suggestions are not fulfilled, we are sure Qlik evaluates them carefully. And most importantly, give back to the community. Every one of us needed to start somewhere and many of us started by searching the Qlik Community website for solutions to our own problems at hand, learning about all those amazing blogs, etc. If you’re considering applying for Qlik Luminary, you certainly have so much to share. And it does NOT have to be technical. Maybe you developed a user enablement content, or Qlik Center of Excellence concept, or else. Just show off your enthusiasm.

Favorite thing about Qlik?

There are actually three: Speed, flexibility, and the “Power of grey”. The fact that Qlik is a one-stop-shop for transforming AND visualizing data enables you to build very rapidly, quickly adapt to evolving requirements which evolve often due to the effect of the grey data. “How come THAT is not connected to my selection? Can you tell me more?” How many times have you heard this question?

Can you tell us about a project you’re currently working on using Qlik

There are a few. I am finishing a transition of a couple of QlikView dashboards to Qlik Sense. I was particularly proud of one of those QV dashboards, even featured it on Qlik Gallery (https://community.qlik.com/t5/Qlik-Gallery/EMARK-Hospital-Overview/ba-p/1649837) and it was quite challenging to migrate it to Sense. I also participate in a rather large project for one of the Scandinavian capitals, where we build tons of dashboards based on data from ServiceNow and other systems and embed them into the ServiceNow portal.

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

I am a father of 1.5 daughters, which can be a full-time job. I am also a hobby beekeeper, managing a couple of beehives, where I learn a lot from these tiny creatures. Apart from sweet honey, bees produce tons of data as well if you wire them with the right sensors. This connects two of my big hobbies: bees and Qlik. But the most important thing I am learning from bees is to think green (and now I don’t mean Qlik green). Bees (and insects in general) are on the decline and we need to stop hurting them.

Name a song you have completely memorized.

There are just too many (and I exclude kids’ songs), most of them are in Slovak, so you wouldn’t know them anyway.

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

“Can someone pour me a drink? I feel cold.”

 

Interested in learning more about Juraj Mišina? Be sure to follow him on his social media handles listed below and be sure to stay tuned for episode five!

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

 

LinkedIn: https://www.linkedin.com/in/jurajmisina/

Twitter: @jurajmisina

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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.