DWH INFORMATION

1. what is a hot file, why we need in datawarehousing, where we used in general
Answer

Hot File:If we generate a report from two different
database, at that time we go for Hot File.The only drawback
is it will occupy the whole space in the hard disk.

Need of DWH:if u want enterprise reporting and analysis
from your historical data.

2.What is ?Data mining??
Answer

It may be also defined as a Science of extracting use full
information from large datasets or databases.

Data mining is a process of extracting useful information
from huge amounts of enterprize data.

3.What are Fact tables and Dimension Tables?
Answer

Fact table: It contains numeric values and also contain
composite key(i.e collection of foreign key) e.g.. sales
and profit.
Dimension table: It contains character values E.g
Customer_name,Customer_city.


A fact table typically has two types of columns: those that
contain facts and those that are foreign keys to dimension
tables. facts may be composed of measures,degenerated
dimensions.The primary key of a fact table is usually a
composite key that is made up of all of its foreign keys

Dimension tables, also known as lookup or reference tables,
contain the relatively static data in the warehouse.
Dimension tables store the information you normally use to
contain queries. Dimension tables are usually textual and
descriptive and you can use them as the row headers of the
result set. Examples are customers or products


4.When should one use an MD-database (multi-dimensional database) and not a relational one?
Answer

1 Because More than one dimensions can be shareble for Other
Department

2 The Physical Load will be less.

3 Less Complexity of Fact



5. What is subject area?

In OBI presentation layer, we represent logical area's
where each area represents a start schema.\
we can drag and drop varios attributes to answer area for
quering it.
this area calles subject area


6. what is data validation strategies for data mart validation after loading process
Answer

direct(faster)
loads data first then validates with keys and avoids
records without reference while indexing


7.DWH architecture?
Answer

it is composed of dataware house
layer,datastagelayer,process management layer,meta data
layer,application layer and other etc


8.What is factless fact schema?
Answer

A fact table without any measure is called factless fact.


9.How can Oracle Materialized Views be used to speed up data warehouse queries?
Answer

In oracle materialized view carry the carry with them so it
is easy 7 faster to retrieve the data for reporting instead
of goin to the actual database these provide the faster
retrieval of data.


In data warehouses, you can use materialized views to
precompute and store aggregated data such as the sum of
sales.
Materialized views are often referred to as summaries,
because they store summarized data. They can also be used
to precompute joins with or without aggregations.

A materialized view eliminates the overhead associated with
expensive joins and aggregations for a large or important
class of queries



10.what are the types of dimension tables
Answer
# 3

There are many dimension tables.
The commonly used are
Confirmed dimension,
Junk dimension,
Degenerated dimension,
Slowly changing dimension,
Rapidly changing dimension

The others are
Virtual dimension,
Regular dimension,
Casual dimension,
Shared dimension,
monster dimension.
These are used on certain condtions


11.Explain about Control M JObs detaily?How to execute this.
Answer

Control M Consist of Many Jobs that are use for :-

Enabiling the down AgentNode(CTMUENA*)

Pinging the down AgentNode(CTMUPNG*)

Disabiling any AgentNode(CTMUDIS*)

List Job which is use for checking availability or
unvailaibility for particular Server in Control M
CTMULST*
(Command that is use for this particular job is
ctm_agstat -LIST '*'| grep-i available|unavailable)

There are many other control M jobs that are use for
different-2 purposes.



12.what is the difference between aggregate table and fact table ? how do you load these two tables ?
Answer

The difference that i know is that the aggregate tables
contain only the summaries of the data where as the fact
tables contain summaries and measures. i.e.,the grain of
the data present in fact table is more than the grain of
the data present in aggregate tables.


A fact table typically has two types of columns: those that
contain numeric facts (often called measurements), and
those that are foreign keys to dimension tables. A fact
table contains either detail-level facts or facts that have
been aggregated. Fact tables that contain aggregated facts
are often called summary tables or aggregated fact. A fact
table usually contains facts with the same level of
aggregation. Though most facts are additive, they can also
be semi-additive or non-additive. Additive facts can be
aggregated by simple arithmetical addition. A common
example of this is sales. Non-additive facts cannot be
added at all. An example of this is averages. Semi-additive
facts can be aggregated along some of the dimensions and
not along others. An example of this is inventory levels,
where you cannot tell what a level means simply by looking
at it.


13.What is confirmed dimension?
Answer

a dimension which is shared by all fact tables that is
confirmed dimension


Confirmed Dimension is, which can be reusable across
multiple data marts.