Redefining Big Data: More Than A Buzzword

We all use the term, but what does it really mean? I ask 2015 Qlik Luminary Dalton Ruer.

By now everybody has heard of big data and ironically nobody can agree on a singular definition! You can find big data discussed in news articles, case studies…blog posts.

It’s even in TV advertisements during sporting events featuring celebrities. Big data is pretty much everywhere. I think it’s probably worth taking a step or two back and re-examining the use of the term.

Data is one of the most valued commodities today for businesses of all sizes. Some industries generate data quicker than others but what’s most important is knowing how to use that data. You can learn a lot from the trends and indicators within increasingly larger sets of data – but when you don’t know how to search it or even how to index it…then what do you do?

I brought this topic to someone that knows the struggle all too well: self-proclaimed Qlik Dork (and 2015 Qlik Luminary) Dalton Ruer, BI Architect for Northeast GA Health System. I took a few minutes of Dalton’s time last month to reflect back on his struggle to pull insights from his organization’s data and his take on what big data actually means:

Q: Are there any absolutes when it comes to the use of data? Where does big data fit in?

A: It’s funny, data is just a bunch of 0s and 1s until it’s presented in a meaningful way. A lot of people want to reduce the time it takes to analyze the data; but they aren’t taking the time to think about how truthful that data is. Is it something you can defend? What if your boss wants to see it and asks that next level question: are you prepared? That’s the area where a lot of data metrics stumble. Big data plays a part in this too. You can make the case to your superiors that you have all the information you will ever need – but the real key is how you consume it and analyze it.

Q: OK, what is the best way to consume and analyze that data: is there a single process or software suite?

A: There’s no one way that works for everybody, but there is one thing that everybody can agree on: if you don’t know what you’re looking at? You’re in trouble. There needs to be a desire to want to learn how to use forward-looking tools for business intelligence. Buy books, bring in business analysts, whatever it takes – no more passing the buck! The beauty of using business intelligence software for our organization: we can see ALL the data then slice and dice it when we need it, even on a mobile device.

What is exactly does #bigdata mean? We ask the @QlikDork for his thoughts

Q: What kind of data are you pulling in using Qlik?

A: We have pulled in eight years of patient history into multiple QlikView apps. Northeast GA Health System receives over 800,000 hospital visits a year and roughly 300 Emergency Department visits per day. We struggled previously because four years ago we were generating reports built by our IT department (painstakingly) over the course of 20 years. The problem with those reports is that with thousands to choose from: people couldn't find the ones they wanted. Even if they found a report with the right input parameters there was no way to know what criteria was being used on the back end. That leads to a room full of people each holding a different report!

Q: So that’s where the consumption of data caused an issue?

A: Exactly. Once we started using Qlik, we had access to all the data at once and we were able to reset charts or filter them as needed when people would ask follow-up questions, imagine that! What’s really cool is that previously we only knew what the standard reports told us but now we can actually start debunking myths.

For example, let’s say we wanted to look at the efficiency of treatment for Emergency Department patients. Previously, we would have static reports generated at different intervals but now we have the tools to look deeper at various factors: length of stay, time from waiting room to bed, time to completion of lab work, etc. Once we have those figures we can start to put the puzzle together of how we are performing based on patient feedback and comparing these figures to our retention rate. This has given us the ability to positively adjust our staffing based on the peak times that we see patients entering the ER. We can be predictive as opposed to being reactive. It’s knowledge through useful action.

Honestly: when you don’t have analytics, the rest is just hearsay.

I want to thank Dalton for taking the time to chat with us about Northeast GA Health System. For more helpful tips and tricks on visualizing all of your organization’s data, check out his blog: Qlik Dork.


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