Online Business Intelligence Fall 2020

Over the last two months, we have travelled the field of Business Intelligence. The journey started off by describing commonalities and differences among the concepts of Business Intelligence, Big Data, Analytics, and Data Science, and considering the paradigm shift that Big Data means for data analytics. Moving forward, we continued our journey to discuss data warehouses, dashboard design, web analytics, and network analysis in harnessing the power of business intelligence. This blog is the last one in my series on business Intelligence. It revisits the main themes in MIS 587 and ends with my final thoughts, including my reflection on best practices for data analysis in business intelligence.  Data Warehouse Design Module 1 included such diverse topics as performance management (the Balanced Scorecard was the technique of choice here), development of Key Performance Indicators, fundamentals of Online Analytical Processing and Online Transaction Processing, design of data warehouse...

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...