Online Business Intelligence Fall 2022

  Introduction This blog covers topics discussed during weeks two through four, which all relate to data warehouse design. Below is a list of each topic and summaries of my understanding for each. Any related materials and readings will be included in each section as well as my thoughts on how they relate to lectures.  Data Warehouse Design Cycle . In a nutshell, this is about how data from  OLTP (or several transactional sources) is grabbed and processed for the the OLAP, with lots of ETLs in between. Both the OLTP and the OLAP have important roles in the data warehouse ecosystem--the OLTP is record-oriented while OLAP has aggregated type of queries. Kimball breaks down the cycle to four components and refers to it as the DW/BI Architecture. In addition to the OLTP (Kimball calls these source systems), the other components are the ETL systems, data presentation areas, and BI applications. The first step in designing a DW/BI is to consider the needs of the business.   Balance Scorecard

Week one lectures introduced us to Big Data and Business Intelligence. The term ‘big’ is described by volume (amount of data), velocity (speed of data), and variety (range of data sources and types); there is a lot of information ubiquitously floating everywhere. How we digitally exist gives organizations an opportunity to learn patterns on who we are and calculate the probability of how we’ll act. The case studies in Big Data Gets Personal discussed how only .5% of what we share over the Internet is harvested by organizations, and the rest remains unstructured and untapped. The process of leveraging useful data is where Business Intelligence comes in. In the McKinsey Global Institute white paper, it emphasizes that the “physical and digital worlds are converging.” Almost everyone in the world uses social applications, and organizations are creatively finding new ways of engaging their stakeholders within these apps. Even the simplest idea of datafying ‘likes’ on a product will help

Hello Colleagues,  My name is Kat Francisco, and I have worked at the University of Arizona for nearly 15 years. I'm from the Bay Area, California but now call Sahuarita, Arizona home with my husband, two boys, and cat. My kids play baseball and piano, so when I'm not at tournaments, games, and recitals... well that's pretty much where I am at, so I really appreciate the days when nothing is on the calendar. I do make time for classes, faculty/staff intramural softball, and I crochet. If you happen to be on campus and see a crocheted cactus, it's probably one that I made. 🌵 My job at the university is nontechnical in theory, but as we quickly learned from this class, one needs data to process, interpret, and make informed decisions--for any job, really. In my position, it's more about using information as evidence, like proof that our instructors have the proper qualifications to teach and that those instructors continue to be productive. Another example is to