MIS 3150 Exam 1

Force 1-4

Force 1 - Generative and Agentic AI

Force 2 - Lakehouse Convergence

Force 3 - Real Time Everything

Force 4 - Governed and Regulated Data

Generative and Agentic AI

Force 1

agents plan, retrieve, call tools and self-correct

Watch For- retrieval quality and tool design becoming analytics problems

Lakehouse Convergence

Force 2

storage argument settles

from storage into catalogs and governance

watch for - the catalog, not the file format being the thing that traps you

Real Time Everything

Force 3

change data capture plus streaming SQL is replacing the nightly batch job as default

Watch for- “How fresh is this number?” becoming a routine business question

Governed and Regulated Data

Force 4

regulations

Watch for- lineage and access control shaping design before performance does

Big Data

Volume, Velocity, Variety, Veracity, Value

Volume

large amounts

Velocity

data arrives continuously

streaming SQL brough sub second processing within reach of ordinary teams

Variety

Tabular, semi-structured, and unstructured data collection

Veracity

trustworthiness, completeness and lineage

formalized into “data contracts” between producers and consumers

Value

business outcome obtained from the data

increasingly measured casually, not just displayed on a dashboard

Data

raw observations, signals, and measurements

Information

data given structure, context, and meaning

knowledge

patterns connected into something you can act on

wisdom

knowing which questions are worth asking at all

five types of analytics

Descriptive, Diagnostic, Predictive, Prescriptive, Generative

Descriptive analytics

what happened?

aggregation and dashboards

Power BI, Tableau

Diagnostic

Why did it happen?

Drill down and correlation

statistical notebooks

Predictive

What will happen?

Regression, classification, forecasting

Prescriptive

What should we do?

optimization and simulation

Generative

What should we produce?

large language models and code generation

traditional analytical set up

Source systems (OLTP, ERP, CRM, LOB) →

Staging and ETL (extract, transform, load) →

Data warehouse (single source of truth, database designed for analysis) →

BI and Analytics (Dashboards and Reporting)