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Final Thoughts

                The past eight weeks have surprisingly flown by. I came into this class expecting something exceptionally difficult (based on MIS 531 being a prerequisite) and I was pleasantly surprised to instead find a thoughtful, engaging class waiting for me. Although not entirely what I expected MIS 587 has been an interesting ride and I’ve learned quite a bit, both new information and solidifying concepts I was already aware of from work and other classes. In the paragraphs below, I’ll outline some of what I have learned, how I think I can applying in my career, and general thoughts about the class and information imparted. I will say for the record that this portion of the class, the social media engagement, has been a unique experience. We have an expectation as students that there will be some discussion component to any course (and especially in an online course, a written discussion component). Using the standard D2L message board is boring. Forcing us all to engage on soc
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Network Analysis

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In this week's lectures we learned the basics of Network Analysis. This is a very fascinating area of study and although I have some exposure to network analysis from previous course work I'm just thrilled by the possibilities and am eager to dive in. As internet usage proliferates further and further and proliferates, as we advance toward a holistic internet of things, we are increasingly engaging with others in new and meaningful ways and the networks we form can yield tremendous insight into our lives. To be able to tap those networks and analysis the data therein has huge implications not just for business but all analytical fields. In our first lecture we discussed the basics of what networks are. Defined as a collection of entities and the relationships among them, networks quite literally are our every interaction quantified into graph form. Each individual in a network, be they a person or a website, is a vertex, and every interaction or relationship is an edge. These
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Web Analytics and Broader Applications

In this week's lectures we discussed both web analytics in general and the google analytics platform specifically. In Lecture 9 we define web analytics as the analysis of data obtained through a website. This data is usually collected via cookies which record a visitor's activity as they access, navigate through, interact with, and eventually leave an organization's website. Once collected, we can use the Web Analytics Cycle to process and analyze the collected data. This includes setting goals for the organization, determining if those goals are being met, gathering reports on the collected web data,  analyzing those reports, and making recommendations to improve the organization's website/s to meet those goals. We utilize the 5 "w's" in analyzing web data: who, what, when, where, and why (we also capture how, which has some uses I will discuss later).  In Lecture 10 we walk through the Google Analytics platform. Google Analytics is a free web ana
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Database Management and Dashboard Construction

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Over the past few weeks since the first blog we've covered a huge amount of material, which is really no surprise for an 8 week class. Though we move fast and furious through our material it never fails to be interesting, thought provoking, and applicable in fairly diverse ways. I noticed one of my classmates used Tableau to visualize the bodycount for HBO's hit bloodbath (show) Game of Thrones, and if that doesn't stand out like a novel application then I don't know what does! It's certainly inspiring me to attempted my own mapping of pop culture; probably something to with the character connections from one of those great, sprawling historical epics. Dickens maybe. Or The Wire. In the meantime, let's look back on what we've done so far. In Week 2 we considered the Balanced Scorecard, which is essentially a framework with which to define business goals. A Balanced Scorecard helps define key performance indicators (KPI) and important metrics, and how to ma
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First Post - Gotta start somewhere

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By way of an introduction, my name is Anson Smith (pleased to meet you), and I came here to party (and by party I mean learn about Big Data). I work QA at a local education technology company, a position I scored through grit, raw brainpower, and critical thinking skills acquired in my otherwise useless pursuit of a BA in East Asian Studies. Japan Focus, from the University of Arizona. Considering I have a deep love of technology and am apparently good at things IS/IT/BI/Dev adjacent, I thought getting my MS in MIS would be a good way to solidify those skills and showcase my abilities with shiny credentials. In my spare time I enjoy hiking, reading literally anything, the occasional video game, traveling, and biking. But at my heart I'm a nerd. So what does that have to do with anything? My nerd-dom is at the heart of why I am here; I LOVE this stuff. Technology. Computers, Internet of Things, wearable tech, I love it all. I like to consider myself an early adopter; if there's
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