Data Warehousing Interview questions
Data Warehousing Interview - posted on August 07, 2008 at
17:10 pm by Rajmeet Ghai
Answer -
A data warehouse can be considered as a storage area where interest specific or
relevant data........
Answer - As mentioned, data in a warehouse comes from the
transactions. Fact table in a data warehouse consists........
Answer - ETL is Extract Transform Load. It is a process of
fetching.........
Answer - Data warehousing is merely extracting data from
different sources, cleaning the........
Answer - OLTP: Online Transaction and Processing helps and
manages applications based........
Answer - A data cube stores data in a summarized version which
helps in a faster analysis of data..........
Answer - A snowflake Schema in its simplest form is an
arrangement of fact tables.........
Answer - Analysis service provides a combined view of the data
used in OLAP.........
Answer - Sequence clustering algorithm collects similar or
related paths, sequences of data.........
Answer - Discreet data can be considered as defined or finite
data..........
Answer - Time series algorithm can be used to predict
continuous values of data.......
Answer - XMLA is XML for Analysis which can be considered as a
standard for accessing data in OLAP.......
Answer - Data Warehousing helps you store the data while
business intelligence.....
Answer - Dimensional modeling is often used in Data
warehousing.......
Answer - Data warehouses commonly use a surrogate key.......
Answer - Fact less tables are so called because they simply
contain........
Answer - A fact table is usually designed at a low level of
Granularity...........
Answer - A snow flake schema design is usually more complex
than a start schema.....
Answer - A view is created by combining data from different
tables........
Answer - A data cube stores data in a summarized version which
helps in a faster analysis............
Answer - In scenarios where certain data may not be appropriate
to store in....
Answer - Stages of a data warehouse helps to find and
understand.......
Data Warehousing Interview - posted on May 11, 2009 at
14:40 pm by Vidya Sagar
The aggregate view of complete data inventory is provided by Virtual
Warehousing........
The transactional data captured and reposited in the Active Data Warehouse......
Dependent data ware house are build........
Designing a model for data or database is called data modelling........
Dimensional modelling is very flexible for the user perspective........
A snapshot of data warehouse is a persisted report from the catalogue.........
The dimensions that are persisted in the fact table is called dimension
table.........
Data Mart is a data repository which is served to a community of people.......
Metadata describes about data. It is ‘data about data’. It has information about
how and when......
The following are the methods of loading dimension tables.......
The following are the differences between OLAP and data warehousing......
The primary keys of entity tables are the foreign keys of dimension
tables.......
A transformer built set of similar cubes is known as cube grouping. A single
level in one dimension......
Slowly changing dimension target operator is one of the SQL warehousing
operators......
The simplest data warehousing schema is star schema.......
Star Schema: A de-normalized technique in which one fact table is associated
with several dimension tables.......
At the time of updating the data warehouse, a lookup table is used.......
The combination of real-time activity and data warehousing is called real time
warehousing.......
Allowing having same names in different tables is allowed by Conformed
facts.......
The facts that can not be summed up for the dimensions present in the fact table
are called non-additive facts.......
A BUS schema is to identify the common dimensions across business
processes......
The differences between SAS and other tools are......
Statistical Analysis System is an integration of various software products which
allows the developers to perform.......
Data cleaning is also known as data scrubbing. Data cleaning is a process which
ensures the set of data is correct and accurate......
A column (usually granular) is called as critical column which changes the
values over a period of time.......
Data cube is a multi-dimensional structure. Data cube is a data abstraction to
view aggregated data from a number of perspectives........
Also read
What is SQL Server 2005 Analysis Services (SSAS)?
What are the new features with SQL Server 2005 Analysis Services (SSAS)?
What are SQL Server Analysis Services cubes?
Explain the purpose of synchronization feature provided in Analysis Services
2005.
Explain the new features of SQL Server 2005 Analysis Services (SSAS). [Hint -
Unified Dimensional Model, Data Source View, new aggregation functions and
querying tools]....................
Explain the concepts and capabilities of Business Intelligence.
Name some of the standard Business Intelligence tools in the market.
Explain the Dashboard in the business intelligence.
SAS Business Intelligence.
Explain the SQL Server 2005 Business Intelligence components..........
Explain the concepts and capabilities of Business Object.
What is Business object agent?
What is broad cast agent?
Explain the functional differences between BO and COGNOs.
What is a universe? Explain the types of universes in business objects.
What is security domain in Business Objects?............
Differentiate between Data Mining and Data warehousing.
What is Data purging?
What are CUBES?
What are OLAP and OLTP?
What are the different problems that “Data mining” can solve?
What are different stages of “Data mining”?.....................
Explain the concepts and capabilities of OLAP.
Explain the functionality of OLAP.
What are MOLAP and ROLAP?
Explain the role of bitmap indexes to solve aggregation problems.
Explain the encoding technique used in bitmaps indexes.
What is Binning?
What is candidate check?..................
More datawarehousing interview
questions - March 22, 2010 at 15:20 PM by Kshipra
What is a data warehouse? What are its qualities?
What are the components of datawarehouse?
Explain: a.) Multidimensional Database b.) Relational Database
How would you decide on using them?
Define Datamarts. Is it preferable to load data from datawarehouse to datamarts
or otherwise. Why?
How would you purge data from cache in different ways?
What are database triggers? How would you manage them in DWH?
Explain SCD. What are the different methods to capture them?
Explain: a.) E-R modeliing b.) Dimensional Modelling c.) Semi addictive facts
d.) Hierarchies e.) Level
Explain: a.)OLAP b.) Datawarehouse c.) ODS d.) OLTP
What do you mean by a fact less fact table?
What do you mean by snapshot?
Why is denormalization promoted in Universe Designing?
Will you be able to load a fact table if its star index is gets corrupted? If
yes, how?
What do you mean by non-addictive facts?
What are different types of OLAP technologies? List advantages and
disadvantages of each.
What are the various architectures of data warehouse? Which is used where?
Is there a difference between data warehousing and business intelligence? If
yes, what?
Compare data warehouse and operational
data.
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