May 10, 2019

Srikaanth

Apple SSAS Interview Questions Answers

What is AMO?

The full form of AMO is Analysis Managament Objects. This is used to create or alter cubes from .NET code.

After creating the cube, if  we added a new column to the OLTP table then how you add this new attribute to the cube?

Just open the datasourceview and on right click we find the option REFRESH. Click the REFRESH then it will add new attributes to the table which can be added to Cube.

REAL TIME INTERVIEW QUESTIONS –

 What is the size of the Cube in your last Project?

Answer to this question varies from project to project and mainly depends on how BIG is your database and how COMPLEX the database design is. Generally for the database with a TRANSACTION TABLE of 50 crore records, the cube size will be around 100GB. So, better go with 100GB as answer to this question.

What is size of the database in your last Project?

You can expect this question immediately after you answer 100GB to the last question. The database size will be 600 to 800GB for which the cube will come to 100 GB. So go with 800GB for this question.

What is size of the fact(Transaction) table in your last Project?

This will be the next question if you answer 800GB as your dataabase size. Here he is not expecting SIZE in GBs but the interviewer will be expecting NUMBER OF ROWS in the Transaction table. Go with 57Crore records for this question.
Apple Most Frequently Asked Latest SSAS Interview Questions Answers
Apple Most Frequently Asked Latest SSAS Interview Questions Answers

How frequently you process the cube?

You have to be very careful here. Frequency of processing cube depends on HOW FREQUENTLY YOU ARE GETTING NEW DATA. Once the new data comes then SSIS team loads it and send a mail to SSAS team after load is completed successfully. Once SSAS team receives the mail then these guys will look for best time to PROCESS.
Typically we get data either Weekly or Monthly. So you can say that the processing of the cube will be done either Weekly or monthly.

How frequently you get DATA from clients?

This answer should be based on your last answer. IF you answered WEEKLY to last question then the Answer to this question also should be WEEKLY. IF MONTHLY for last question then this answer also should be MONTHLY.

What type of Processing Options you used to process the cube in your Project?

This is the toughest question to answer. This depends on DATA you have and CLIENTS requirements. Let me explain here.
If the database is SMALL, let’s say it has only 1 crore records then people do FULL PROCESS as it wont take much time.
If the database is MEDIUM, let’s say it has only 15 crore records then people prefer to do INCREMENTAL PROCESS unless CLIENTS ask us to do FULL PROCESS as it takes little bit of time.
If the database is HUGE, let’s say it has more than 35 to 40 crore records then people prefer to do INCREMENTAL PROCESS unless CLIENTS ask us to do FULL PROCESS as it takes lot of time. In this case we TRY to convince clients for INCREMENTAL and if they don’t agree then we don’t have any other option.
Incremental process will come into picture ONLY when there is no updates to the OLD data i.e no changes to already existing data else NO OTHER OPTION than FULL PROCESS.

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

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.

https://mytecbooks.blogspot.com/2019/05/apple-ssas-interview-questions-answers.html
Subscribe to get more Posts :