Hyoun Park is the Chief Research Officer of Blue Hill Research where he oversees day-to-day research operations, delivery and methodology focused on vendor and technology selection. In addition, Park covers analytics and enterprise mobility technologies as a noted advisor, social influencer, and practitioner. Park has been named as a top 10 Big Data, analytics, and mobility influencer including quotes in USA Today, the Los Angeles Times, and a wide variety of industry media sources.
Hyoun will be speaking on the topic of The Data Supply Chain: Maximizing Value Throughout the Cycle at the PASS Business Analytics Conference in Santa Clara, CA, April 20-22.
Recently, we sat down with Hyoun to learn about his views on the analytics industry today.
Tell us your data story: How did you first become interested in working with data, and what path did you take to where you are today?
My first real experiences with data came from being an undergraduate biochemistry student, where I started learning about how to model computational chemistry challenges. In learning how to structure, model, and analyze data, I quickly found that these tools were also useful for an incredibly important use case: fantasy baseball predictions. I switched gears and started working on a fantasy baseball website called mosey.com, the first fantasy baseball website, where I wrote articles and created statistical projections. That initial work has stuck with me to this day where I now work as an industry research analyst who still write articles and papers on the current state of technology based on relevant models and frameworks.
As Chief Research Officer of Blue Hill Research, what excites you most in the world of data research and analytics?
Although there are a lot of aspects to choose from, I’d say that the most interesting aspect is the increasing use of graph data and networks to analyze connections between data points. The interactions between specific data points are often difficult to analyze through traditional data structures, so we still have a poor understanding of basic network behavior on collaboration and the quality of business processes. Between improved network analysis and better vector analysis, we can finally figure out how the strength and interconnectedness of nodes truly affect the overall value of a network.
If you were going to recommend one must-have skill for business analytics professionals to learn in 2015, what would it be?
Storytelling. If you cannot fit your data and visualizations into a compelling and consistent narrative, the right people will never get the message and your perfect analysis will be in vain. Whether you’re working on data structure, business intelligence, or analytics, focus on the business story and the part enhanced through your efforts.
In the process of translating data into business insights as part of an analytics project, what is the first question that you ask?
Who wants the data? There are many ways to cleanse data and to pursue quantitative accuracy, but it is more important (and faster!) to make the data relevant and directionally accurate for the correct stakeholder than to be perfectly accurate and completely irrelevant to your audience.
As an expert in social media analytics, what’s the biggest mistake that you see organizations make when analyzing their social media data?
Companies spend too much time focusing on the quantity of interactions. The key to social is not to simply get a basic “like”, but to build ongoing interaction and communication. If your social “friends” are not regularly interacting with you and sharing your perspective with their communities, you are not relevant even if you have a million “friends.” Better to have 1,000 great advocates than 1,000,000 disinterested acquaintances.
If you were building out an analytics team, what skillset and traits would you be looking for?
Call me old-fashioned, but I still want to start with data warehousing, ETL, and report building skills: the traditional structured data analytics. But I also want a developer who can translate these analytic outputs into applications. I need the statistician to provide forecasting and predictive analysis. And I want Hadoop and NoSQL expertise so that I can deal with Big Data challenges that will come from the Internet of Things, text, and other high volume and high traffic data. And I want a data artisan who can create fantastic static and interactive visualizations. So, I want a lot!
Who is your data hero and why?
The irony is that my data hero isn’t very good at data or analytics, but I would choose Bill James, the famous baseball analyst. Although he’s not a DBA or data analyst, he had a very specific gift in looking at baseball data and figuring out the right questions to ask. Based on that, he would often find the answer through brute force methods of calculation than an elegant analyst could have found in seconds. But at the end of the day, I think it is more important to ask the right questions and use the right data sources than to be the best modeler or developer.
Learn more with Hyoun – catch his session The Data Supply Chain: Maximizing Value Throughout the Cycle at the PASS Business Analytics Conference in Santa Clara, CA, April 20-22.