Online Business Intelligence Fall 2020

The topic of Module III: Network Analysis has a special meaning to me. I have worked and teach a bit on networks and accessibility. In my case, on ground transportation networks and spatial distribution of assets in the urban environment. These networks are usually planar, and links are constrained by the spatial location of the nodes and by the costs of constructing (and maintaining) the transportation infrastructure. Other physical networks (aerial, maritime, logistical) are less constrained by the physical determinants of the connections (see Rodrigue, 2020): No doubt, the topologies of social networks can get much more complex! Apart from that, I would say that the vast majority of metrics about the geometry and structure of a network (and the process of solving an optimization problem in a network environment) are pretty similar in transportation and social networks. For example, there are technical equivalences in solving least-cost paths, Hamiltonian paths, and service areas ...

In the last module, we spent a good part of the time reflecting on topics of web analytics and metrics to assess website performance for business purposes. As we saw at the beginning of the module, web analytics is the “objective tracking, collection, measurement, reporting, and analysis of quantitative Internet data to optimize websites and web marketing initiatives” (Web Analytics Association – It seems to be a defunct organization in 2020), and a plethora of metrics have been developed in the last 30 years for that purpose.   Web Metrics: Occam’s Razor by Avinash Kaushik   As I was reading about different audiences, traffic channels, visitor behavior, and business outcomes, I ended up exploring the blog of Avinash Kaushik: Occam’s Razor . The number of topics and perspectives in this blog is beyond what I could read in a single week of coursework, though I believe all these topics are tidily discussed in his two bestsellers: Web Analytics, One Hour a Day and Web Anal...

Module 1 has covered quite a bit of ground on data analytics in the context of Business Intelligence. Its content covers a few main topics, namely, Data Warehouse Design & Star Schema Design, Performance Management & Balanced Scorecard, Data Quality Analysis, and Dashboard Design and Analysis. This article overviews the four questions. Data warehouse Design & Star Schema Design The module started off by introducing the notion of data warehouses and data marts, and the data design system known as Dimensional Modeling (Kimball et al. 2016). The essential protocol for dimensional modeling involves (1) defining the business process, (2) declaring the grain of the model (i.e., events where data are collected from), (3) identifying its dimensions (i.e., its context), and (4) identifying its measurable facts. An important characteristic of dimensional modeling is its support of database design where database normalization is largely avoided. As Kimball and Ross (2013) put it, ...

Hi all:  Module 0 of this course introduces fundamental concepts of big data and business intelligence. I would highlight the shift of paradigm in data science caused by big data as the main take-away in this unit. This shift involves the "datafication " of the world (many more things are being tracked), richer and more dynamic information (production of data and information is growing rapidly), and the "N=All" notion (the entire population of data is available so sampling is not required). I think there may be cases where communities are not yet well represented in the data (so models may be biased), but this might change in the future as IT becomes more popular and pervasive in human life. I found two articles, MIT’s Big Data Gets Personal and MGI’s Ten IT-enabled business trends , to be especially interesting, not only for the huge possibilities of business intelligence, big data and machine learning for human development, but also for the ethical questions th...

Hi 587ers! My name is Fernando and I am taking this course as part of the BI Certificate at the U of A.  I am originally from Spain, in the southwestern corner of Europe, and currently live in Tucson, Arizona. Below, I include a picture of my hometown, Alicante.  I specialize in Geographic Information Systems and have been working in academia for about 15 years now. Thanks to my work, I have got to live in several regions of the globe. After a few years getting to know the European peoples and some time in Japan, I moved to the USA for research collaborations with the US Department of Agriculture. More recently, I have been teaching at the University of Montana and the University of Arizona. I am quiet interested in the most recent developments in data analytics, and how business intelligence and big data could be used in combination with GIS for spatial analysis. Looking forward to starting this course and chatting with you all!