Reminders:
Connect due Friday 11pm – 2 chapters, 2 things each
Thursday will be an in-class group exercise. Be here!

Decisions – you’ve already made 100 decisions decisions today
Simple decisions (structured) – based on data (what to eat, wear) – For a store – Inventory replenishing
Complex (unstructured) – Why go to college? Why UMB?
Medium (semi-structured) – Why MSIS110?

From a business standpoint:
Simple – Letting students get into a section of MSIS110 (room capacity)
Medium – How many sections of 110 to offer
Complex – What shoould our curriculum look like?

Formal book terms:
Operational – Day to day
Managerial – Medium term
Strategic – Long term

KPI – Key Performance Indicators – GPA. Acceptance Rate. Graduation Rate. Job Placement.
CSF – Critical Success Factors – How to get there
ROI – Return on Investment. Increased salary for your career? Build a warehouse?

Kinds of systems that companies have

• Transaction Processing Systems – TPS; OLTP (online transaction processing); POS (Point of Sale) (vs Batch systems). Capture data to a database and record it as a transaction, Accumulate Data
• Online Analytical Processing – “What if” systems, Turning Data into Information – Like the amazon ratings, or which employees are showing up on time
• Decision Support Systems – Managerial to help understand what’s going on in a business. Often Drill down so can get details about details.
• Executive Information Systems – Highest level. Not that different than DSS despite book

Restaurant TPS vs DSS
– Orders, Supplies/Managing Stock, Hours worked,
– Total orders, Hours worked, Inventory value

Parallels to data/information/knowledge

Artificial Intelligence – Ai used to be mostly about Expert Systems – Replicate human thinking in
a very narrow focus (like 20 questions or even Deep Blue for chess)

Now AI is more about machine learning, or neural networks – the computer learns and draws conclusions based on data alone. Self driving cars, Jeopardy, AlphaGo (https://www.youtube.com/watch?v=WXuK6gekU1Y&t=2s)

But – What about AI Bias? Race & gender biases have all been proven to live inside these new thinking machines!

Note – Book talks about AR and VR as AI – I think they’re more just a trick of hardware these days, not so much intelligence. Where do you draw the line between good tech & intelligent tech???