Online Business Intelligence Fall 2024

In this week’s lectures, I learned about the fundamentals of network analysis. A network consists of vertices (also called nodes) that represent entities, and edges that define the relationships between these nodes. For instance, a node might represent a person, such as "Jill," and an edge could represent the relationship between Jill and another person, like "Andrew," where Jill follows Andrew. These relationships can be directed (one-way) or undirected (mutual) and can be weighted (indicating the strength of the relationship) or unweighted. The lecture also introduced the concept of single-mode networks and two-mode networks. In a single-mode network, all the nodes represent the same type of entity (e.g., people), while a two-mode network connects two different types of entities (e.g., people and Facebook pages). After the lecture, I came across an interesting article on Medium titled Visualizing My Facebook Network Clusters by Ashris (https://towardsdatascience.c...

For this post, I wanted to analyze the concepts from Module 2 and apply them to real-life examples that my classmates and I might encounter. My first example, the web analytics cycle and the five W's of web analytics, comes from my experience in logistics. While I’ve primarily applied these concepts in a different field, I now see the advantages of using them in my current role, especially for optimizing specific tasks. My second example, related to types of web traffic, draws on the recent election, a time when many individuals experienced various forms of targeted communication, such as phone calls, ads on YouTube, and personal research to learn more. For the task completion rate, I was inspired by a quiz question, which made me reflect on how many email subscriptions I’ve signed up for to save 10%, or how often I find myself searching for coupons while checking out online. I also thought about how some stores don’t offer the most user-friendly mobile websites. Applying these con...

Lecture Summary: Week 2: Data Warehouse Design and Balanced Scorecard In Week 2, we learned foundational frameworks for using data in decision-making, focusing on data warehouse design and the Balanced Scorecard (BSC). The distinction between OLTP (Online Transaction Processing) and OLAP (Online Analytical Processing) was highlighted, with OLAP supporting strategic analysis through aggregate queries. Key processes like ETL (Extract, Transform, Load) and data marts were discussed, along with the role of the Operational Data Store (ODS) in ensuring data accuracy. The Balanced Scorecard (BSC) is a performance management tool that measures organizational performance from four key perspectives: Learning and Growth, Internal Processes, Customer, and Financial. This holistic approach helps align business activities with strategic goals and encourages focus on both long-term objectives and short-term execution. Finally, dimensional modeling and star schema design were introduced as techniq...

Self-Introduction Hello everyone! My name is Alena Kusok, and I’m excited to embark on this journey with all of you in MIS 587. I’m currently a systems engineer at Raytheon, where I’ve been working for almost two years. I graduated from Eller with a bachelor’s degree in MIS in 2023, and I’m eager to deepen my knowledge and skills in Business Intelligence throughout this course. As someone who enjoys applying information systems knowledge in my work, I see this course as an excellent opportunity to advance my career. I’m particularly interested in how BI techniques can uncover valuable insights from both internal transactional data and external “Big Data.” I hope to gain hands-on experience with tools like Tableau and Google Analytics to develop key performance indicators and enhance my understanding of web analytics. I’m excited to see how the knowledge gained from this course will help me not only in my current role but also in potential future opportunities in corporate positions. In...