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Pretest Data Warehouse Modelling

Total questions: 25

Worksheet time: 13mins

Name
Class
Date
1.

The term Data Warehouse was coined by Bill Inmon in 1990, which

he defined in the following way:

a)

"A warehouse is a subject-oriented, integrated, stable and volatile collection of data in support of management's decision making process".

b)

"A warehouse is a subject-oriented,integrated, time-variant and non-volatile collection of data in support of management's decision making process".

c)

Both A and B

d)

None of above

2.

Which is difficult topic in this unit?

a)

OLAP SERVER

b)

DATA WAREHOUSING ARCHITECTURE

c)

STAR SCHEMA

d)

FACT CONSTELLATION

3.

Definition of Subject Oriented Data: Data that gives information about a particular subject

instead of about a company's ongoing operations.

a)

True

b)

False

4.

Definition of Integrated Data: Data that is gathered into the data warehouse from a variety of sources and merged into a coherent whole.

a)

True

b)

False

5.

Your opinion about use of ROLAP and MOLAP.

4 lines
6.

Benefits of Data warehousing are:

1. Data warehouses are designed to perform well with aggregate queries running on large amounts of data.

2. The structure of data warehouses is easier for end users to navigate, understand and query against unlike the relational databases primarily designed to handle lots of transactions.

3. Data warehouses enable queries that cut across different segments of a company's operation. E.g. production data could be compared against inventory data even if they were originally stored in different databases with different structures.

4. Queries that would be complex in very normalized databases could be easier to build and maintain in data warehouses, decreasing the workload on transaction systems.

5. Data warehousing is an efficient way to manage and report on data that is from a variety of sources, non uniform and scattered throughout a company.

6. Data warehousing is an efficient way to manage demand for lots of information from lots of users.

a)

1,2,4,6

b)

1,3,2,5

c)

1,2,3,4

d)

1,2,3,4,5,6

7.

Select easiest topic in this unit

a)

OLTP vs OLAP

b)

OLAP servers

c)

Architecture

d)

Schemas

8.

Operational Data is:

a)

Focusing on transactional function such as bank card withdrawals and deposits

b)

Detailed

c)

Updateable and Reflects current data

d)

All of above

9.

Explain Data mart with example

4 lines
10.

Informational Data is:

a)

Focusing on providing answers to problems posed by decision makers

b)

Summarized

c)

Non updateable

d)

All of above

11.

Hive created by

a)

Facebook

b)

Google

c)

Amazon

d)

Yahoo!

12.

Hive is a

a)

Data Warehousing Tool

b)

DataBase Management Tool

c)

Data Scrapping Tool

d)

Hadoop Data Tool

13.

Hive don't make use of following:

a)

HDFS for Storage

b)

MapReduce for Execution

c)

Stores metadata in a RDBMS

d)

GPU for Processing

14.

HQL is ______________ to SQL

a)

Similar

b)

Dissimilar

15.

Hive __________ SQL queries _________ MapReduce Jobs

a)

create, convert into

b)

compiles, into

c)

execute, from

d)

interpret, of

16.

Which of them is not hive feature?

a)

easy to code

b)

support rich datatypes

c)

supports group-by

d)

UDF not supported

17.

A database is namespace for

a)

tables

b)

fields

c)

records

d)

keys

18.

Separation of data on basis of specific attribute is

a)

Partition

b)

Bucketting

c)

Fragmentation

d)

Slicing

19.

Separation of data on basis of mathematical hash function is

a)

Partition

b)

Bucketting

c)

Fragmentation

d)

Slicing

20.

What is the right visual charter of HIVE Application?

a)
b)
c)
d)
21.

What hive is not

a)

online transaction processing

b)

Data Warehousing tool

c)

Similar to SQL

d)

Analyze log data

22.

Hive is suitable for

a)

real-time queries

b)

row-level updates

c)

queries over small data sets

d)

analyze historical data

23.

Applications of Apache Hive

a)

Log processing

b)

OLTP

c)

Billing systems

d)

Processing Web Forms

24.

Hive enables easy data summarization, ad-hoc querying and analysis of large volumes of data.

a)

true

b)

false

25.

In _________ due to equal volumes of data in each partition, joins at Map side will be quicker.

a)

bucketing

b)

partitioning