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The General Sql Server Interview Questions consists the most
frequently asked questions in Sql server. This list of 100+ questions guage
your familiarity with the Sql Server platform. The q&a have been
collected over a period of time from various blogs, forums and other
similar Php sites
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5. Data Warehousing Interview Question Part[1]
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| 5.1
What is Data Warehousing?
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| 5.2
What are fundamental stages of Data Warehousing?
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| 5.3
What is Dimensional Modeling?
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| 5.4
What is Fact table?
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| What
is Dimension table?
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| 5.6
What are the Different methods of loading Dimension tables?
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| 5.7
What is OLTP?
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| 5.8
What is OLAP?
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| 5.9
What is the difference between OLTP and OLAP?
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| 5.10
Describes the foreign key columns in fact table and dimension table?
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| 5.11
What is Data Mining?
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| 5.12
What is the difference between view and materialized view?
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| 5.13
What is ER Diagram?
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| 5.14
What is ODS?
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| 5.15
What is ETL?
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| 5.16
What is VLDB?
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| 5.17
Is OLTP database is design optimal for Data Warehouse?
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| 5.18
If de-normalized is improves data warehouse processes, why fact table is in
normal form?
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| 5.19
What are lookup tables?
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| 5.20
What are Aggregate tables?
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5.1 What is Data Warehousing?
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A data warehouse is the main repository of an organization's historical data,
its corporate memory. It contains the raw material for management's decision
support system. The critical factor leading to the use of a data warehouse is
that a data analyst can perform complex queries and analysis, such as data
mining, on the information without slowing down the operational systems
(Ref:Wikipedia). Data warehousing collection of data designed to support
management decision making. Data warehouses contain a wide variety of data that
present a coherent picture of business conditions at a single point in time. It
is a repository of integrated information, available for queries and analysis.
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5.2What are fundamental stages of Data Warehousing?
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Offline Operational Databases -Data warehouses in this initial stage are
developed by simply copying the database of an operational system to an
off-line server where the processing load of reporting does not impact on the
operational system's performance. Offline Data Warehouse -Data
warehouses in this stage of evolution are updated on a regular time cycle
(usually daily, weekly or monthly) from the operational systems and the data is
stored in an integrated reporting-oriented data structure Real Time Data
Warehouse - Data warehouses at this stage are updated on a transaction or event
basis, every time an operational system performs a transaction (e.g. an order
or a delivery or a booking etc.) Integrated Data Warehouse - Data warehouses at
this stage are used to generate activity or transactions that are passed back
into the operational systems for use in the daily activity of the
organization.;
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5.3 What is Dimensional Modeling?
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Dimensional data model concept involves two types of tables and it is different
from the 3rd normal form. This concepts uses Facts table which contains the
measurements of the business and Dimension table which contains the
context(dimension of calculation) of the measurements.
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5.4 What is Fact table?
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Fact table contains measurements of business process. Fact table contains the
foreign keys for the dimension tables. Example, if you are business process is
"paper production", "average production of paper by one machine" or "weekly
production of paper" will be considered as measurement of business process.
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5.5 What is Dimension table?
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Dimensional table contains textual attributes of measurements stored in the
facts tables. Dimensional table is a collection of hierarchies, categories and
logic which can be used for user to traverse in hierarchy nodes.
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5.6 What are the Different methods of loading Dimension tables?
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There are two different ways to load data in dimension tables.
Conventional (Slow) : All the constraints and keys are validated against
the data before, it is loaded, this way data integrity is maintained.
Direct (Fast) : All the constraints and keys are disabled before the
data is loaded. Once data is loaded, it is validated against all the
constraints and keys. If data is found invalid or dirty it is not included in
index and all future processes are skipped on this data.
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5.7 I What is OLTP?
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OLTP is abbreviation of On-Line Transaction Processing. This system is an
application that modifies data the instance it receives and has a large number
of concurrent users.
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5.8 What is OLAP?
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OLAP is abbreviation of Online Analytical Processing. This system is an
application that collects, manages, processes and presents multidimensional
data for analysis and management purposes.
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5.9 What is the difference between OLTP and OLAP?
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Data Source OLTP: Operational data is from original data source of the data
OLAP: Consolidation data is from various source. Process Goal OLTP: Snapshot of
business processes which does fundamental business tasks OLAP:
Multi-dimensional views of business activities of planning and decision making
Queries and Process Scripts OLTP: Simple quick running queries ran by users.
OLAP: Complex long running queries by system to update the aggregated data.
Database Design OLTP: Normalized small database. Speed will be not an issue due
to smaller database and normalization will not degrade performance. This adopts
entity relationship(ER) model and an application-oriented database design.
OLAP: De-normalized large database. Speed is issue due to larger database and
de-normalizing will improve performance as there will be lesser tables to scan
while performing tasks. This adopts star, snowflake or fact constellation mode
of subject-oriented database design. Back up and System Administration OLTP:
Regular Database backup and system administration can do the job. OLAP:
Reloading the OLTP data is good considered as good backup option.
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5.10 Describes the foreign key columns in fact table and dimension table?
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Foreign keys of dimension tables are primary keys of entity tables. Foreign
keys of facts tables are primary keys of Dimension tables.
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5.11 What is Data Mining?
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Data Mining is the process of analyzing data from different perspectives and
summarizing it into useful information.
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5.12 What is the difference between view and materialized view?
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A view takes the output of a query and makes it appear like a virtual table and
it can be used in place of tables. A materialized view provides indirect access
to table data by storing the results of a query in a separate schema object.
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5.13 What is ER Diagram?
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Entity Relationship Diagrams are a major data modelling tool and will help
organize the data in your project into entities and define the relationships
between the entities. This process has proved to enable the analyst to produce
a good database structure so that the data can be stored and retrieved in a
most efficient manner. An entity-relationship (ER) diagram is a specialized
graphic that illustrates the interrelationships between entities in a database.
A type of diagram used in data modeling for relational data bases. These
diagrams show the structure of each table and the links between tables.
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5.14 What is ODS?
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ODS is abbreviation of Operational Data Store. A database structure that is a
repository for near real-time operational data rather than long term trend
data. The ODS may further become the enterprise shared operational database,
allowing operational systems that are being reengineered to use the ODS as
there operation databases.
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5.15 What is ETL?
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ETL is abbreviation of extract, transform, and load. ETL is software that
enables businesses to consolidate their disparate data while moving it from
place to place, and it doesn't really matter that that data is in different
forms or formats. The data can come from any source.ETL is powerful enough to
handle such data disparities. First, the extract function reads data from a
specified source database and extracts a desired subset of data. Next, the
transform function works with the acquired data - using rules orlookup tables,
or creating combinations with other data - to convert it to the desired state.
Finally, the load function is used to write the resulting data to a target
database.
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5.16 What is VLDB?
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VLDB is abbreviation of Very Large DataBase. A one terabyte database would
normally be considered to be a VLDB. Typically, these are decision support
systems or transaction processing applications serving large numbers of users.
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5.17 WIs OLTP database is design optimal for Data Warehouse?
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No. OLTP database tables are normalized and it will add additional time to
queries to return results. Additionally OLTP database is smaller and it does
not contain longer period (many years) data, which needs to be analyzed. A OLTP
system is basically ER model and not Dimensional Model. If a complex query is
executed on a OLTP system, it may cause a heavy overhead on the OLTP server
that will affect the normal business processes.
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5.18 If de-normalized is improves data warehouse processes, why fact table is
in normal form?
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Foreign keys of facts tables are primary keys of Dimension tables. It is clear
that fact table contains columns which are primary key to other table that
itself make normal form table.
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5.19 What are lookup tables?
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A lookup table is the table placed on the target table based upon the primary
key of the target, it just updates the table by allowing only modified (new or
updated) records based on thelookup condition.
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5.20 What are Aggregate tables?
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Aggregate table contains the summary of existing warehouse data which is
grouped to certain levels of dimensions. It is always easy to retrieve data
from aggregated tables than visiting original table which has million records.
Aggregate tables reduces the load in the database server and increases the
performance of the query and can retrieve the result quickly.
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