Sitel Most Frequently Asked Latest SSAS Interview Questions Answers

What is use of IsAggregatable property?

In Analysis Service we generally see all dimension has All member. This is because of IsAggregatable property of the attribute. You can set its value to false, so that it will not show All member. Its default member for that attribute. If you hide this member than you will have to set other attribute value to default member else it will pick some value as default and this will create confusion in browsing data if someone is not known to change in default member.

What are key, name and value columns of an attribute?

Key column of any attribute: Contains the column or columns that represent the key for the attribute, which is the column in the underlying relational table in the data source view to which the attribute is bound. The value of this column for each member is displayed to users unless a value is specified for the NameColumn property.

Name  column of an attribute: Identifies the column that provides the name of the attribute that is displayed to users, instead of the value in the key column for the attribute. This column is used when the key column value for an attribute member is cryptic or not otherwise useful to the user, or when the key column is based on a composite key. The NameColumn property is not used in parent-child hierarchies; instead, the NameColumn property for child members is used as the member names in a parent-child hierarchy.

Value columns of an attribute: Identifies the column that provides the value of the attribute. If the NameColumn element of the attribute is specified, the same DataItem values are used as default values for the ValueColumn element. If the NameColumn element of the attribute is not specified and the KeyColumns collection of the attribute contains a single KeyColumn element representing a key column with a string data type, the same DataItem values are used as default values for the ValueColumn element.

What is hierarchy, what are its types and difference between them?

A hierarchy is a very important part of any OLAP engine and allows users to drill down from  summary levels hierarchies represent the way user expect to explore data at more detailed level

hierarchies  is made up of multipule levels creating the structure based on end user requirements.

->years->quarter->month->week ,are all the levels of calender hierarchy

They are 2 types of hierarchies they are

Natural hierarchy
Unnatural hierarchy
 Natural hierarchy: This means that the attributes are intuitively related to one another. There is a clear relationship from the top of the hierarchy to the bottom.

Example: An example of this would be date: year, quarter and month follow from each other, and in part, define each other.

Unnatural hierarchy: This means that the attributes are not clearly related.

Example: An example of this might be geography; we may have country -> state -> city, but it is not clear where Province might sit.

What is Attribute hierarchy?

An attribute hierarchy is created for every attribute in a dimension, and each hierarchy is available for dimensioning fact data. This hierarchy consists of an “All” level and a detail level containing all members of the hierarchy.

you can organize attributes into user-defined hierarchies to provide navigation paths in a cube. Under certain circumstances, you may want to disable or hide some attributes and their hierarchies.

What is use of AttributeHierarchyDisplayFolder property ?

AttributeHierarchyDisplayFolder: Identifies the folder in which to display the associated attribute hierarchy to end users. For example if I set the property value as “Test” to all the Attributes of a dimension then a folder with the name “Test” will be created and all the Attributes will be placed into the same.

What Is Factless Fact Table?

This is very important interview . The “Factless Fact Table” is a table which is similar to Fact Table except for having any measure; I mean that this table just has the links to the dimensions. These tables enable you to track events; indeed they are for recording events.

Factless fact tables are used for tracking a process or collecting stats. They are called so because, the fact table does not have aggregatable numeric values or information. They are mere key values with reference to the dimensions from which the stats can be collected

Sitel Most Frequently Asked Latest SSAS Interview Questions Answers

What Is Fact Table?

A fact table contains the basic information that you wish to summarize. The table that stores the detailed value for measure is called fact table. In simple and best we can define as “The table which contains METRICS” that are used to analyse the business.

It consists of 2 sections

Foregine key to the dimesion
measures/facts(a numerical value that used to monitor business activity)

What Is Dimension Table?

A dimension table contains hierarchical data by which you’d like to summarize. A dimension table contains specific business information, a dimension table that contains the specific name of each member of the dimension. The name of the dimension member is called an “attribute”

The key attribute in the dimension must contain a unique value for each member of the dimension. This key attribute is called “primary key column”

The primary key column of each dimension table corresponding to the one of the key column  in any related fact table.

How Will You Add A New Column To An Existing Table In Data Source View?

By using named calculations we can add a new column to an existing table in the data source view.

Why We Need Named Queries?

A named query is used to join multiple tables, to remove unnecessary columns from a table of a database. You can achieve the same in database using Views but this Named Queries will be the best bet whe you don’t have access to create Views in database.

What Is Named Query?

Named query in DSV is similar to View in Database. This is used to create Virtual table in DSV which will not impact the underlying database. Named query is mainly used to merge the two or more table in the datasource view or to filter columns of a table.

How Many Types Of Dimensions Are There And What Are They?

They are 3 types of dimensions

confirm dimension
junk dimension
degenerate attribute

How Many Types Of Attribute Relationships Are There?

They are 2 types of attribute relationships they are

Rigid
Flexible
Rigid: In Rigid relationships  where the relationship between the attributes is fixed, attributes will not change levels or their respective attribute relationships.
Example: The time dimension. We know that month “January 2009” will ONLY belong to Year “2009” and it wont be moved to any other year.
Flexible :   In Flexible relationship between the attributes is changed.
Example: An employee and department. An employee can be in accounts department today but it is possible that the employee will be in Marketing department tomorrow.