Brainscape's Knowledge GenomeTM


Top Flashcards (Certified)
All Flashcards

Business Intelligence / Data Mining > Lecture 4 > Flashcards

Lecture 4 Flashcards

1
Q

OLTP?

A

Online Transaction Processing

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

OLAP

A

Online Analytical Processing

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

Where is OLTP used?

A

E-commerce
Banking
Airline Reservations

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

OLTP (User facing)

A

Real-Time
Low latency
Highly-concurrent

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

OLTP (Tasks)

A

Relatively small set of standard transactional queries

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

OLTP (Data access pattern)

A

Random leads
Updates
Writes

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

Where is OLAP used?

A

Business intelligence

Data mining

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

OLAP (Back-end processing)

A

Batch workloads

Less concurrency

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

OLAP (Tasks)

A

Complex analytical queries

Ad-hoc

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

OLAP (Data access pattern)

A

Table scans

Large amounts of data involved per query

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

OLAP Example?

A

Amazon analyzes purchases by its customers to come up with an individual screen with products of likely interest to the customer

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

Downsides of co-existing OLTP and OLAP workloads?

A

Poor memory management
Conflicting data access patterns
Variable latency

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

Solution for having both OLTP and OLAP with no downsides?

A

Separate databases
User-facing OLTP database for high-volume transactions
Data warehouse for OLAP workloads

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

How to connect OLTP with OLAP?

A

ETL

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

What does ETL stand for?

A

Extract
Transform
Load

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

`What is Data Warehouse?

A

A physical repository where relational data are specially organized to provide enterprise-wide, cleansed data in a standardized format

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

Characteristics of DWs?

A 
Subject oriented
Integrated
Time-variant
Nonvolatile
Summarized
Not normalized
Metadata
Web based
Client/server
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

What is Data Mart?

A

A departmental small-scale DW that stores only limited/relevant data

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

Two types of Data Mart?

A

Dependent data mart

Independent data mart

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
20
Q

Dependent data mart?

A

A subset that is created directly from a data warehouse

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
21
Q

Independent data mart?

A

A small data warehouse designed for a strategic business unit or a department

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
22
Q

Other DW Components?

A

ODS
Oper marts
EDW
Metadata

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
23
Q

ODS?

A

Operational Data Stores

A type of database often used as an interim area for a data warehouse

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
24
Q

Oper Marts?

A

An operational data mart

25
EDW?
Enterprise Data Warehouse | A data warehouse for the enterprise
26
Metadata?
Data about data
27
Types of DW Architectures?
Three-Tier Architecture | Two-Tier Architecture
28
Three-Tier Architecture?
1. Data acquisition software (backend) 2. The DW that contains the data and the software 3. Client (Front-end) software that allows users to access and analyze data from the warehouse
29
Two-Tier Architecture?
First two tiers in 3Tier architecture are combined into one
30
Example of Three-Tier Architecture?
Client Workstation Application Server Database Server
31
Example of Two-Tier Architecture?
Client workstation | Application and database server
32
What does Web-based DW Architecture contain?
Client (Web browser) Web server -> Web pages Application server Data warehouse
33
Data warehouse development approaches?
Inmon Model | Kimball Model
34
Inmon Model?
EDW approach (top-down)
35
Kimball Model?
Data mart approach (bottom-up)
36
Characteristics of DM approach?
One subject area Months to develop Costs 10k to 100k plus Low to medium difficulty Data prerequisite is common within the business area Sources include only some operational and external systems Size can range from megabytes to gigabytes Time horizon - near current and historical data Data transformation - low to medium
37
Characteristics of EDW approach?
Several subject areas Years to develop Costs 1mil plus Hard difficulty Data prerequisite is common across the enterprise Sources include many operational and external systems Size can range from gigabytes to petabytes Time horizon - historical data Data transformation - high
38
Tables in DW?
Fact table | Dimensional tables
39
Fact table?
A very large accumulation of facts such as sales
40
Dimension tables?
Smaller, generally static information about the entities involved in the facts
41
Representation of Data in DW?
Dimensional Modelling Star Schema Snowflakes Schema
42
Dimensional Modelling?
A retrieval-based system that supports high-volume query access
43
Star Schema?
The most commonly used and the simplest style of dimensional modeling Contain a fact table surrounded by and connected to several dimension tables
44
Snowflakes Schema?
An extension of star schema where the diagram resembles a snowflake in shape
45
What is multidimensionality?
The ability to organize, present, and analyze data by several dimensions, such as sales by region, by product
46
Multidimensional presentation contents?
Dimensions Measures Time
47
Dimensions?
``` Product Salespeople Market Segments Business units ```
48
Measures?
Money Sales volume Head count Inventory profit
49
Time?
Daily Weekly Monthly
50
Two classes of fact-table attributes?
Dimension attributes - The key of a dimension table Dependent attributes - A value determined by the dimension attributes of the tuple
51
Warehouse Data Models?
Relations Stars and snowflakes Cubes
52
Warehouse Operators?
Slice and dice Roll-up, drill down Pivoting Other
53
Slice?
A subset of a dimensional array
54
Dice?
A slice on more than two dimensions
55
Drill down/Up?
Navigating among levels of data ranging from the most summarized (up) to the most detailed (down)
56
Roll Up?
Computing all of the data relationships for one or more dimensions
57
Pivot?
Used to change the dimensional orientation of a report or an ad hoc query-page display
58
ROLAP?
Relational Online Analytical Processing
59
MOLAP?
Multi-Dimensional Online Analytical Processing

Business Intelligence / Data Mining (7 decks)

Brainscape helps you reach your goals faster, through stronger study habits.
© 2025 Bold Learning Solutions. Terms and Conditions