Chapter 1 Flashcards
Types of Business Analytics
Descriptive
Predictive
Prescriptive
Descriptive Business Analytic: Questions
What happened?
What is happening?
Descriptive Business Analytic: Enablers
- Business Reporting
- Dashboards
- Scoreboards
- Data warehousing
Descriptive Business Analytic: Outcomes
well-defined business problems and opportunities
Predictive Business Analytic: Questions
What will happen?
Why will it happen?
Predictive Business Analytic: Enablers
- Data mining
- Text mining
- Web/media mining
- Forecasting
Predictive Business Analytic: Outcomes
Accurate projections of future events and outcomes
Prescriptive Business Analytic: Questions
What should I do?
Why should I do it?
Prescriptive Business Analytic: Enablers
- Optimization
- Simulation
- Decision modeling
- Expert systems
Prescriptive Business Analytic: Outcomes
Best possible business decisions and actions
Define data wharehouse
- collection of databases storing content and historical data
- “single version of truth”
What are the components of data warehousing process?
- data sources
- ETL Process
- Enterprise data warehouse
- Metadata
- Data mart
- API/Middleware tools
OLTP: Purpose
to carry out day-to-day business functions
OLTP: Data source
- transaction database
- a normalized data repository
- focused on efficiency and consistency
OLTP: Reporting
- routine
- periodic
- narrowly focused
OLTP: Database requirements
ordinary rational databases
OLTP: Execution speed
- fast
- recording of business transactions and routine reports
OLAP: Purpose
- to support decision making
- to provide answers for business and management queries
OLAP: Data source
- data warehouse or data mart
- a non-normalized data repository
- focused on accuracy and complenetess
OLAP: Reporting
- Ad hoc
- multidimensional
- broadly focused
OLAP: Database requirements
- multiprocessor
- large-capacity
- specialized
OLAP: Execution speed
- slow
- resource intensive, complex, large-scale queries
Olap opperations: Slice
a susset if data corresponding to a single value set for one or more dimensions not in the subset
OLAP operations: DICE
slice on more than two dimentions
What are some other OLAP operations?
- Drill Down/up
- Roll up
- Pivot
What is the Drill Down/Up (other OLAP operations)?
navigation among levels of data ranging from the most summarized to the most detailed
What is the Roll Up (other OLAP operations)?
computing all of the data relationships for one or more dimensions
What is the Pivot (other OLAP operations) used for?
to change dimensional orientation of a report or an ad hoc
Simon’s model (chart)
What is a Problem and what does it require?
- root cause
- requires solutions for solving, substantive and tangible impact
What is a symptom?
s visible recognizable sign of underlying problem, indication, observable effect
What are DSS?
interactive computer-based systems wich support decision makers by utilization of data and models to solve semi structured problems
What is data mining?
process that uses statistical, mathemathical and artificial intelligence techniques to extract and identify information
Types of patterns
- Association (link analysis, etc)
- Prediction (classification, time series, regression)
- Segmentation (clustering)
What are the learning types?
- Supervised (know classes)
- Unsupervised (unkown classes)
What is the purpose of data science?
covers practical application of advanced analytics, statistics and encessary preparation in business context
