Chapter 1

Question 1

Types of Business Analytics

Answer 1

Descriptive
Predictive
Prescriptive

Question 2

Descriptive Business Analytic: Questions

Answer 2

What happened?
What is happening?

Question 3

Descriptive Business Analytic: Enablers

Answer 3

• Business Reporting
• Dashboards
• Scoreboards
• Data warehousing

Question 4

Descriptive Business Analytic: Outcomes

Answer 4

well-defined business problems and opportunities

Question 5

Predictive Business Analytic: Questions

Answer 5

What will happen?
Why will it happen?

Question 6

Predictive Business Analytic: Enablers

Answer 6

• Data mining
• Text mining
• Web/media mining
• Forecasting

Question 7

Predictive Business Analytic: Outcomes

Answer 7

Accurate projections of future events and outcomes

Question 8

Prescriptive Business Analytic: Questions

Answer 8

What should I do?
Why should I do it?

Question 9

Prescriptive Business Analytic: Enablers

Answer 9

• Optimization
• Simulation
• Decision modeling
• Expert systems

Question 10

Prescriptive Business Analytic: Outcomes

Answer 10

Best possible business decisions and actions

Question 11

Define data wharehouse

Answer 11

• collection of databases storing content and historical data
• “single version of truth”

Question 12

What are the components of data warehousing process?

Answer 12

• data sources
• ETL Process
• Enterprise data warehouse
• Metadata
• Data mart
• API/Middleware tools

Question 13

OLTP: Purpose

Answer 13

to carry out day-to-day business functions

Question 14

OLTP: Data source

Answer 14

• transaction database
• a normalized data repository
• focused on efficiency and consistency

Question 15

OLTP: Reporting

Answer 15

• routine
• periodic
• narrowly focused

Question 16

OLTP: Database requirements

Answer 16

ordinary rational databases

Question 17

OLTP: Execution speed

Answer 17

• fast
• recording of business transactions and routine reports

Question 18

OLAP: Purpose

Answer 18

• to support decision making
• to provide answers for business and management queries

Question 19

OLAP: Data source

Answer 19

• data warehouse or data mart
• a non-normalized data repository
• focused on accuracy and complenetess

Question 20

OLAP: Reporting

Answer 20

• Ad hoc
• multidimensional
• broadly focused

Question 21

OLAP: Database requirements

Answer 21

• multiprocessor
• large-capacity
• specialized

Question 22

OLAP: Execution speed

Answer 22

• slow
• resource intensive, complex, large-scale queries

Question 23

Olap opperations: Slice

Answer 23

a susset if data corresponding to a single value set for one or more dimensions not in the subset

Question 24

OLAP operations: DICE

Answer 24

slice on more than two dimentions

Question 25

What are some other OLAP operations?

Answer 25

- Drill Down/up - Roll up - Pivot

Question 26

What is the Drill Down/Up (other OLAP operations)?

Answer 26

navigation among levels of data ranging from the most summarized to the most detailed

Question 27

What is the Roll Up (other OLAP operations)?

Answer 27

computing all of the data relationships for one or more dimensions

Question 28

What is the Pivot (other OLAP operations) used for?

Answer 28

to change dimensional orientation of a report or an ad hoc

Question 29

Simon's model (chart)

Answer 29

Question 30

What is a Problem and what does it require?

Answer 30

- root cause - requires solutions for solving, substantive and tangible impact

Question 31

What is a symptom?

Answer 31

s visible recognizable sign of underlying problem, indication, observable effect

Question 32

What are DSS?

Answer 32

interactive computer-based systems wich support decision makers by utilization of data and models to solve semi structured problems

Question 33

What is data mining?

Answer 33

process that uses statistical, mathemathical and artificial intelligence techniques to extract and identify information

Question 34

Types of patterns

Answer 34

1. Association (link analysis, etc) 2. Prediction (classification, time series, regression) 3. Segmentation (clustering)

Question 35

What are the learning types?

Answer 35

1. Supervised (know classes) 2. Unsupervised (unkown classes)

Question 36

What is the purpose of data science?

Answer 36

covers practical application of advanced analytics, statistics and encessary preparation in business context