Quiz 4 Flashcards
1
Q
business applications
A
- Function orientation
- Process-centric
- Goal: Efficient execution of business operations while maintaining data integrity
2
Q
business applications examples
A
- Order processing
- Payroll processing
- Maintaining inventory
- Accounts receivable
3
Q
operational databases
A
- support day-to-day business activities
- optimized for transaction processing
4
Q
transaction
A
- well-defined process that occurs in exactly the same way and is routine (i.e. repeats)
- produce one set of data (i.e. record(s))
- characterize one single operation – i.e. is indivisible (Atomic)
5
Q
transaction processing
A
- chronological processing of transactions
- aims to data changes (Insert, Update, Delete) immediately upon completion of transaction
- aims to maintain data integrity
6
Q
business decision making:
What kinds of decisions are made?
A
- How to boost sales levels
- Revenues
- Sales Price
- Number of Customers
- How to reduce costs
- Effect of marketing campaigns on product sales
- etc.
7
Q
business decision making:
What level are the decisions being made?
A
- Different individual products
- (ipod, ipad, ipad-2, samsung-tv1, samsung tv-2)
- Different groups of products
- (tablets, apple products, samsung products, televisions)
- Different levels of groupings
8
Q
business decision making:
What type of information is needed for such decisions?
A
- Individual sale transaction is insufficient
9
Q
business decision making:
Decision making in support of Business Objectives
A
Example business objectives:
- Over next year, increase customer based by 20%
- Improve customer retention by 25%
- Increase sales by 15%
- Increase profit by 20%
10
Q
business decision making:
Information Requirements
A
- More than business function needs Enterprise-wide Integrated View
- Timely information delivery
- Data consistency
- Historical Information
11
Q
business decision making:
What would be the characteristics of the queries?
A
- Large number of records
- Historical
- Information across business functions and domains
- (Sales, Marketing, Financials, etc.)
12
Q
information hierarchy
A
[insert graphic]
13
Q
From Silo to Enterprise Wide View graphic
A
14
Q
Data Warehouse Architecture graphic
A
15
Q
How is Data Warehouse different from Operational Database?
A
16
Q
ODB vs. DW:
Data Content
A
ODB:
- current value
DW:
- archived
- historic
- summarized
17
Q
ODB vs. DW:
Data Structure
A
ODB:
- optimized for transaction processing
DW:
- optimized for complex querying
18
Q
ODB vs. DW:
Access Frequency
A
ODB:
- high
DW:
- low
19
Q
ODB vs. DW:
Access Type
A
ODB:
- read
- update
- delete
DW:
- read only
20
Q
ODB vs. DW:
Usage
A
ODB:
- predictable
- routine
DW:
- ad-hoc
- random
- context dependent on decision-making
21
Q
ODB vs. DW:
Response Time
A
ODB:
- sub-seconds
DW:
- several seconds to minutes
22
Q
ODB vs. DW:
Users
A
ODB:
- many
DW:
- few
23
Q
What is ETL?
A
- Extraction
- Transformation
- Loading
24
Q
ETL sources of data
A
- Production Data:
- data from operational systems
- Internal Data:
- data gathered and utilized typical systems
- example: spreadsheets, departmental databases, etc.
- External Data:
- data purchased from outside sources
- Archived Data:
- old data from within the company
- (typically one-time addition)
25
*data staging*
* Characterized by ETL
* Extraction:
* Data from diverse systems and data models
* Transformation:
* Cleaning
* Standardization:
* Data type
* Measurement
* Interpretation (Synonym vs. Homonym)
* Summarization
* Loading
26
*Defining features of data warehouse*
* Subject Orientation
* (vs. Functional Orientation of Operational DB)
* Enterprise-wide Integration
* Time-Variant Data / Historical
* Non-volatile / read-only
* Granularity
27
Defining Features of DW:
*Subject-Orientation*
28
Defining Features of DW:
*Time-Variant*
* Operational database store current values.
* Examples:
* What is the balance owed by customer?
* What is the list price of the car?
* Data warehouse helps analyze changes in outcomes because of changes in dimensions.
* Example:
* to help answer questions like what was the cause of drop in sales.
29
Defining Features of DW:
*Time-Variant allows...*
* Historical analysis
* Analysis of patterns for predictive use
* Impact of decisions in different operational areas
* e.g., marketing on sales, customer retention, profits.
* Measure outcome influence
* e.g., impact of decision to drop prices on revenues, number of customers, …
30
Defining Features of DW:
*Non-Volatile Data*
* Data is moved from operational into data warehouse at intervals of time
* Captured snapshot does not change
* For example:
* balance owed by customer at the time is captured
* any change in balance is loaded next extraction.
* (time variant and nonvolatile)
31
Defining Features of DW:
*Data Granularity*
* defines level of detail
* multiple levels of detail are usually present
* example:
* grocery store may store data in warehouse on:
* hourly intervals
* daily intervals
* weekly …
* customer behavior may be tracked on:
* Individual customer
* Zip code
* Customer type, etc.
32
*metadata*
* metadata is basically Data Dictionary
* often defined as “data about data”
33
*types of metadata*
* Operational
* ETL
* End-User
34
*operational metadata*
* information about source systems
* where the data is coming from
* details of fields used, etc.
35
*ETL metadata*
* extraction methods
* business rules for transformation
* when was data last loaded
* percentage errors, …
36
end-user metadata
* navigational map for end-users
* what information is located where
* what does it mean
* what is the measurement unit, etc.
37
*Operational DB vs. Data Warehouse*
38
Defining Business Requirements:
*Identifying Focus of Decision Support*
* Overall Goal:
* What information is needed for decision making?
* Identifying the Subject:
* What is the outcome being focused on?
* Example: Sales, Inventory
* Analyzing decision making:
* What about the outcome is being analyzed? (measures)
* Measures of success/failure of strategy (decision)
39
*examples of measures*
Decisions involving sales may focus on:
* market share
* number of unique customers
* number of customer visits
* average sales to each customer
* total sales
* profits
* profit margins, …
40
Defining Business Requirements:
*Identifying Business Dimensions of Decisions*
* What are the components of the decision?
* Example:
* *What can the decision maker do to accomplish the outcomes identified?*
* Identify various types decisions that are made to influence the outcome
* Identify the Business Dimensions of these decisions
41
*example business dimensions*
To increase total sales (subject), decision may be taken to launch a promotion campaign offering discounts on...
* PRODUCTS,
* at different STORES,
* on certain DATES.
Note: besides the decision, the outcome measures are also analyzed on the dimensions. Monthly Sales for Product at different stores
42
Defining Business Requirements:
*Hierarchies in Business Dimensions*
Decisions are defined by:
* BUSINESS DIMENSIONS
* LEVEL
* CATEGORY
43
*level*
* level corresponds to different levels of hierarchy within a dimension
* example: Day---\>Month---\>Quarter---\>Year
* the finest level of hierarchy identifies the GRANULARITY of the data
* both decisions taken and outcomes measured can be analyzed up to this level of detail
44
*category*
* categories are dimensions characterized by groupings.
* for example: ethnicity, college education, etc.
45
multi-dimensional data
