Blog 5 | Summary and Reflection of Class
Introduction
This final blog summarizes the work that we have done during the past eight weeks. The course introduced Business Intelligence techniques, and we gained exposure to analytical tools that people in everyday organizations use for decision-making. The class was divided into four modules and the assignments for the modules maps nicely into the six learning outcomes for the course. I’ve listed each one below and described how my experience with the assignment in this class helped to achieve the intended learning for the class.
Learning Outcome 1
Articulate the Characteristics of Big Data beyond the 5 Vs and explain why it is causing a paradigm shift. | I remember three Vs: volume (amount of data), velocity (speed of data), and variety (range of data sources and types). The paradigm shift relates to the datafication and how people are leaving their digital fingerprints in everything. It’s happening so rapidly – feedback is immediate. A mishap on social media can go viral within minutes and get a million comments in short amount of time. Also, there is no more need for sample size since we now have access to full populations. The assignments for this outcome entailed a lot of reading and researching on the web and the assignment that corroborates proof of this outcome is Blog 1, Quiz 1 essays, and the Facebook article posts.
Learning Outcome 2
Clearly describe the role of Business Intelligence in an organization. | Because there is so much data floating everywhere, it is essential for businesses to incorporate people with analytics skills who know how to capitalize on information. Having insight has always been the secret to success, and the need for Business or Data Warehouse Analysts and Data Scientists are high in demand. They are the ones who understand components of business intelligence and how the BI Life Cycle is a continuous and iterative process. The first two learning outcomes relate to Module 0. The concepts learned here were foundational for the technical pieces to follow. It was good to get exposure to BI terms such as data lakes, datafication, and key performance indicators. While researching several articles on the topic, I was impressed to see how organizations displayed their KPIs on their websites. This inspired me to evaluate how we measure the success of program reviews, and I have ideas on how to display key milestones so that deans can see where their units are in the process with meeting deadlines. My hope is that it will inspire units to complete their tasks on time and reduce the number of reminders I need to send.
Learning Outcome 3
Design Data Warehouse Star schemas and understand how OLAP systems are different from OLTP systems. | This section was covered in Module 1 during weeks 2-4. We first learned about the data warehouse design cycle and how balance scorecard is an essential framework for critical management processes—goal setting, business planning, capital allocations, strategic initiatives, and feedback and learning. It changed how businesses measure success and incorporated all aspects of the organization, not just the bottom line. Blog 2 and homework assignment 1 on star schema essentially is proof of learning this outcome. The homework assignment was difficult, and I’m thankful that I had taken MIS 531 Enterprise Data Management and remembered concepts of normalization, cardinality, and entity-relationship diagrams. After submitting the homework, I felt like an expert of OLTP, ELT and OLAP. It was during this module that gained a new hero, Hans Rosling. Yolanda (the TA) is pretty awesome too.
Learning Outcome 4
Develop dashboards to analyze and solve business problems and provide recommendations. | Learning outcomes 3 and 4 relate to Module 1, Data Warehouse Design. This is when the class started to get fun. I’ve seen Tableau dashboards on several websites and have always been impressed with them. I never thought I would have the knowledge to create one myself. This learning outcome is probably one that I will utilize after this class is over and I already have so many ideas on how to incorporate faculty data into a tableau dashboard and embed it into my website at work. The bird strike data was interesting and when I showed my presentation to my colleagues at work, they were totally blown away with my skills and knowledge of bird data.
Learning Outcome 5
Conduct analysis of business websites using Web Metrics and provide recommendations for improving them. | It was really helpful that I have a friend in IT that gave me Google Analytics access to websites at work. I actually conducted a real analysis on the CIRTL website. I was able to work with the director of the program and ask her questions when certain anomalies arose – like why certain people out of state would be interested in viewing a local Arizona program. User engagement is key to having a successful website. Currently, I’m upgrading our website and migrating the pages to a new version of Drupal. We have a really large website and by evaluating the pages and how visitors interact with the pages, we will be able to focus time on enhancing popular pages to maintain its attractivity and archive inactive pages that people don’t find useful anymore. This learning outcome relates to Module 2 and is summarized in Blog 3.
This final blog summarizes the work that we have done during the past eight weeks. The course introduced Business Intelligence techniques, and we gained exposure to analytical tools that people in everyday organizations use for decision-making. The class was divided into four modules and the assignments for the modules maps nicely into the six learning outcomes for the course. I’ve listed each one below and described how my experience with the assignment in this class helped to achieve the intended learning for the class.
Learning Outcome 1
Articulate the Characteristics of Big Data beyond the 5 Vs and explain why it is causing a paradigm shift. | I remember three Vs: volume (amount of data), velocity (speed of data), and variety (range of data sources and types). The paradigm shift relates to the datafication and how people are leaving their digital fingerprints in everything. It’s happening so rapidly – feedback is immediate. A mishap on social media can go viral within minutes and get a million comments in short amount of time. Also, there is no more need for sample size since we now have access to full populations. The assignments for this outcome entailed a lot of reading and researching on the web and the assignment that corroborates proof of this outcome is Blog 1, Quiz 1 essays, and the Facebook article posts.
Learning Outcome 2
Clearly describe the role of Business Intelligence in an organization. | Because there is so much data floating everywhere, it is essential for businesses to incorporate people with analytics skills who know how to capitalize on information. Having insight has always been the secret to success, and the need for Business or Data Warehouse Analysts and Data Scientists are high in demand. They are the ones who understand components of business intelligence and how the BI Life Cycle is a continuous and iterative process. The first two learning outcomes relate to Module 0. The concepts learned here were foundational for the technical pieces to follow. It was good to get exposure to BI terms such as data lakes, datafication, and key performance indicators. While researching several articles on the topic, I was impressed to see how organizations displayed their KPIs on their websites. This inspired me to evaluate how we measure the success of program reviews, and I have ideas on how to display key milestones so that deans can see where their units are in the process with meeting deadlines. My hope is that it will inspire units to complete their tasks on time and reduce the number of reminders I need to send.
Learning Outcome 3
Design Data Warehouse Star schemas and understand how OLAP systems are different from OLTP systems. | This section was covered in Module 1 during weeks 2-4. We first learned about the data warehouse design cycle and how balance scorecard is an essential framework for critical management processes—goal setting, business planning, capital allocations, strategic initiatives, and feedback and learning. It changed how businesses measure success and incorporated all aspects of the organization, not just the bottom line. Blog 2 and homework assignment 1 on star schema essentially is proof of learning this outcome. The homework assignment was difficult, and I’m thankful that I had taken MIS 531 Enterprise Data Management and remembered concepts of normalization, cardinality, and entity-relationship diagrams. After submitting the homework, I felt like an expert of OLTP, ELT and OLAP. It was during this module that gained a new hero, Hans Rosling. Yolanda (the TA) is pretty awesome too.
Learning Outcome 4
Develop dashboards to analyze and solve business problems and provide recommendations. | Learning outcomes 3 and 4 relate to Module 1, Data Warehouse Design. This is when the class started to get fun. I’ve seen Tableau dashboards on several websites and have always been impressed with them. I never thought I would have the knowledge to create one myself. This learning outcome is probably one that I will utilize after this class is over and I already have so many ideas on how to incorporate faculty data into a tableau dashboard and embed it into my website at work. The bird strike data was interesting and when I showed my presentation to my colleagues at work, they were totally blown away with my skills and knowledge of bird data.
Learning Outcome 5
Conduct analysis of business websites using Web Metrics and provide recommendations for improving them. | It was really helpful that I have a friend in IT that gave me Google Analytics access to websites at work. I actually conducted a real analysis on the CIRTL website. I was able to work with the director of the program and ask her questions when certain anomalies arose – like why certain people out of state would be interested in viewing a local Arizona program. User engagement is key to having a successful website. Currently, I’m upgrading our website and migrating the pages to a new version of Drupal. We have a really large website and by evaluating the pages and how visitors interact with the pages, we will be able to focus time on enhancing popular pages to maintain its attractivity and archive inactive pages that people don’t find useful anymore. This learning outcome relates to Module 2 and is summarized in Blog 3.
Learning Outcome 6
Create, visualize, analyze and understand networks and network science as a tool for business analytics. | This learning outcome correlates to Module 3, and we spent the last two weeks learning how to use Gephi, which is a Java-based, open-source graphical visualization software for analyzing networks. The only critique I have of this module is that the tutorials online covered the same things over and over. There are hundreds of introductory tutorials on modularity and community detection—how to change appearances and layouts. I had a really hard time finding a video or instructions on how to get reciprocity. I finally figured it out myself after trying different filters and remembering about ego networks in lecture 11. After submitting the homework assignment IV, I wondered if the CEOs of the Fortune 500 companies would fit into similar communities. People tend to follow each other, like administrators on our campus are friends with other administrators at other institutions, but like Fortune 500 companies, I can’t imagine the University of Arizona following a community college because we’re the big R1, public university—we’re the dominant influencer. The community college, however, would be the follower.
Peer Reviews
Earlier this year, I attended a training seminar for accreditation. The first concept we were introduce with is that higher education is built on the process of peer reviews. It’s used for everything – scholarship, program reviews, accreditation, awards, promotion and tenure, etc. Since then, I have had a different opinion of evaluating my colleagues’ works, like it’s a civic duty, much like voting and serving as a juror. Thus, I understand why we are made to critique our classmates work—it’s the foundation of higher education. To be completely honest though, sometimes the blogs were lazy recaps of the lectures and contributed nothing more, but at least it was a refresher of what was taught. There were several students that put in good, quality work into their blogs, which I enjoyed reading. I really appreciated when students wrote about something personal and applied the work to their own experiences.
Summary
This class completes my requirement for the graduate certificate in Business Intelligence and Analytics. All three classes for the certificate complement each other, but MIS 587 Business Intelligence is my favorite. This class was organized very well and concepts that we learned during the beginning weeks circled back in every assignment… like what would be a KPI? How do we measure? How could this data form questions or be answered? The tools that we experienced with in this class have already contributed and will continue to contribute to my professional work in so many ways. The one major takeaway (and there are several) from this class is the ability to quantify qualitative efforts and display them in a comprehensive and perceptive manner—visually, where no words are needed for quick at-a-glance overview.
This class counts as an elective for the MIS degree and I only have two classes left for that. Overall, I’m really impressed with the MIS program and I understand why it is the number one MIS program in the nation. The concepts and the skills that we learn are essential for organizations, and the need for Business Intelligence employees will only increase. As someone in a non-technical job, I’m wondering how this degree will open up opportunities for me in the future. It’s inspiring to know that several of my classmates are switching jobs—last class a friend accepted with Raytheon, and others are in Academic Analytics. I think I want to explore library science next and move into working as a librarian. Earlier someone posted an article or blog written by someone in library science and I was really impressed--I could do that. There are interesting things happening with the School of Information on campus, so I’ll probably look into their programs soon.
To conclude, thank you Dr. Ram and Yolanda for a wonderful experience. -Kat Francisco
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