Adbase H2 Midterms

Question 1

warehouse is a database designed to enable and support business intelligence (BI) activities, especially analytics.
 intended to perform queries and analysis
 optimized for data retrieval, not for transaction processing
 centralizes and consolidates large amounts of data from multiple sources
 allows organizations to derive valuable business insights from their data to improve decision-making
 can be considered an organization’s “single source of truth”

Answer 1

data warehouse

Question 2

The DW can analyze data about a particular subject or functional area.
 Subjects can be products, customers, departments, regions, etc.
 The functional area can be sales, marketing, finance, distribution, etc.
 Focuses on the data rather than on the processes that modify the data

Answer 2

Subject-Oriented

Question 3

The DW creates consistency among different data types from different sources.

Answer 3

Integrated

Question 4

A student’s level in the database might be defined as “freshman”, “sophomore”, “junior”, or “senior” in the accounting department, and “FR”, “SO”, “JR”, “SR” in the computer information systems department.

Answer 4

Integrated

Question 5

Data in DW represents the flow of data through time. It can be organized weekly, monthly, or annually, etc.

Answer 5

Time-variant

Question 6

Once data is in a data warehouse, it is stable and does not change.

Answer 6

Non-Volatile

Question 7

This is a databank that stocks all enterprise data and makes it manageable for reporting.

Answer 7

Data Warehouse Database

Question 8

 always implemented on the relational database management system (RDBMS) technology like SQL

Answer 8

Data Warehouse Database

Question 9

These tools are used for performing all the conversions, summarizations, and all the changes needed to transform data into a unified format in the data warehouse. These include:
 In case of missing data, populating them with defaults
 Calculating summaries and derived data
 Eliminating unwanted data in operational databases from loading into the data warehouse
 Converting to common data names and definitions

Answer 9

• Extraction, Transformation, and Loading Tools (ETL)

Question 10

is data about data that describes the data warehouse. It provides the source, transformation, integration, storage, usage, relationships, and history of each data element.

Answer 10

Metadata

Question 11

contains information about the warehouse, which is used by data warehouse designers and administrators.

Answer 11

Technical Metadata

Question 12

contains details that give end-users an easy way to understand the information stored in the data warehouse.

Answer 12

Business Metadata

Question 13

Corporate users generally cannot work with databases directly.

Answer 13

• Data Warehouse Access Tools

Question 14

help users produce corporate reports for analysis that can be in the form of spreadsheets, calculations, or interactive visuals.

Answer 14

 Query and reporting tool

Question 15

In such cases, custom reports are developed using application development tools when built-in graphical and analytical tools do not satisfy the analytical needs of an organization.

Answer 15

 Application development tools

Question 16

a process of discovering meaningful new correlations, patterns, and trends by mining a large amount of data. Data mining tools are used to make this process automatic.

Answer 16

Data mining

Question 17

allow users to analyze the data using elaborate and complex multi-dimensional views.

Answer 17

OLAP tools

Question 18

a small, single-subject data warehouse subset that provides decision support for the particular user group.

Answer 18

Data Marts

Question 19

2. Provides consistent information on various cross-functional activities. It is also supporting “blank” reporting and query.

Answer 19

ad-hoc

Question 20

is a data-modeling technique used to map multi- dimensional decision support data into a relational database.

Answer 20

star schema

Question 21

 Star schema has two (2) common components:

Answer 21

Facts table
Dimension table

Question 22

data that will be included in reports and used as the basis of business decisions. It contains measurement or facts to the data and foreign key to dimension table.

Answer 22

Facts table

Question 23

are attributes that qualify and provide more information about facts. It contains dimensions of a fact and they are joined to fact table via foreign key.

Answer 23

Dimension table

Question 24

 a software tool that is used for data analysis and reporting purposes for business decisions
 used by business analysts, managers, and executives. Example: In Netflix, OLAP was used for movie recommendations based on watch history.

Answer 24

• Online Analytical Processing (OLAP)

Question 25

 an operational system that manages the day-to-day transactions of an organization  used by the Database Administrator (DBA) and Database Professionals Example: In ATM centers, OLTP is used for money withdrawals, transfers, deposits, and inquiries.

Answer 25

* Online Transaction Processing (OLTP)

Question 26

Data is processed and viewed as part of a multi-dimensional structure.

Answer 26

* Multi-dimensional data analysis techniques

Question 27

To deliver efficient decision support, OLAP tools must have the following:  Access to many kinds of DBMSs, flat files, and internal and external data sources  Rapid and consistent query response times  Support for very large databases because the data warehouse could easily and quickly grow to multiple terabytes in size

Answer 27

* Advanced Database support

Question 28

permit the user to navigate the data in a way that simplifies and accelerates decision making or data analysis with easy-to-use graphical interfaces

Answer 28

* Easy-to-use end-user interfaces

Question 29

 Works directly with relational databases  Fact and dimension tables are stored as relations.

Answer 29

* Relational OLAP (ROLAP)

Question 30

 extends OLAP functionality to multi-dimensional database management systems (MDBMS)  best suited to manage, store, and analyze multi-dimensional data

Answer 30

* Multi-dimensional OLAP (MOLAP)

Question 31

an extension of the GROUP BY clause that is used to create subtotals and grand totals for a set of columns

Answer 31

* ROLLUP operator

Question 32

Like ROLLUP, this generates subtotals for all the combinations of grouping column s specified in the GROUP BY clause.

Answer 32

* CUBE operator

Question 33

allows you to write a cross-tabulation, which means you can aggregate your results and rotate rows into columns

Answer 33

* PIVOT operator

Question 34

Using the "BLANK" operator, we will display the total number of students enrolled in specific campuses and the grand total of students enrolled in all campuses.

Answer 34

ROLLUP

Question 35

Using the "BLANK operator, we will turn the unique values/rows in the Program column into multiple columns.

Answer 35

PIVOT

Question 36

refers to analyzing massive amounts of data in a data warehouse or other sources to uncover hidden trends, patterns, and relationships. This explains the past and predicting the future for analysis.

Answer 36

Data mining

Question 37

In this step, the goals of the businesses are set, and the important factors that will help in achieving the goal are discovered.

Answer 37

Business Understanding

Question 38

This step will collect the entire data and populate the data in the tool (if using any tool).

Answer 38

Data Understanding

Question 39

This step involves selecting the appropriate data, cleaning, constructing attributes from data, integrating data from multiple databases.

Answer 39

Data Preparation

Question 40

Selection of the data mining technique such as decision-tree, generate test design for evaluating the selected model, building models from the dataset, and assessing the built model with experts to discuss the result is done in this step.

Answer 40

Modeling

Question 41

This step will determine the degree to which the resulting model meets the business requirements. The model is reviewed for any mistakes or steps that should be repeated.

Answer 41

Evaluation

Question 42

In this step, a deployment plan is made. The strategy to monitor and maintain the data mining model results to check for its usefulness is formed. Final reports are also made, and a review of the whole process is done to check any mistake and see if any step is repeated.

Answer 42

Deployment

Question 43

used to retrieve important and relevant information about data and metadata.

Answer 43

Classification

Question 44

used to identify data that are like each other. This process helps to understand the differences and similarities between the data.

Answer 44

Clustering

Question 45

used to identify and analyze the relationship between variables.

Answer 45

Regression

Question 46

used to help find the association between two or more Items. It discovers a hidden pattern in the data set.

Answer 46

Association Rules

Question 47

used to observe data items in the dataset that do not match an expected pattern or expected behavior.

Answer 47

Outer detection

Question 48

used to discover or identify similar patterns or trends in transaction data for a certain period.

Answer 48

Sequential Patterns

Question 49

used to combine other data mining techniques like trends, sequential patterns, clustering, classification, etc. It analyzes past events or instances in the right sequence for predicting a future event.

Answer 49

Prediction

Question 50

* Helps with the decision-making process * Helps companies to get knowledge-based information * Facilitates automated prediction of trends and behaviors as well as the automated discovery of hidden patterns * The speedy process which makes it easy for the users to analyze a huge amount of data in less time

Answer 50

Benefits of data mining