Sql Server Analysis Services (ssas) Interview Questions with Answers
Question: 1. How Many Types Of Dimensions Are There And What Are They?
Answer:
They are three styles of dimensions:
confirm size
junk measurement
degenerate characteristic
Question 2. How Many Types Of Attribute Relationships Are There?
Answer:
They are 2 types of attribute relationships they are
Rigid
Flexible
Rigid: In Rigid relationships wherein the connection among the attributes is constant, attributes will no longer exchange tiers or their respective characteristic relationships.
Example: The time measurement. We realize that month “January 2009” will ONLY belong to Year “2009” and it wont be moved to some other 12 months.
Flexible : In Flexible dating among the attributes is modified.
Example: An worker and department. An employee can be in bills department these days but it’s far viable that the worker may be in Marketing branch tomorrow.
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Question 3. What Is Attribute Relationships, Why We Need It?
Answer:
Attribute relationships are the way of telling the evaluation provider engine that how the attributes are related with each different. It will assist to relate two or greater attributes to every other.Processing time may be reduced if right relationships are given. This will increase the Cube Processing overall performance and MDX question overall performance too.
In Microsoft SQL Server Analysis Services, attributes inside a dimension are continually related both at once or in a roundabout way to the key attribute. When you outline a measurement primarily based on a celeb schema, that is where all measurement attributes are derived from the equal relational desk, an attribute relationship is robotically defined between the important thing attribute and every non-key characteristic of the size.
When you outline a measurement primarily based on a snowflake schema, that’s wherein measurement attributes are derived from a couple of associated tables, an characteristic relationship is routinely defined as follows:
Between the key attribute and every non-key attribute sure to columns within the foremost measurement table.
Between the important thing attribute and the characteristic sure to the overseas key within the secondary desk that hyperlinks the underlying measurement tables.
Between the characteristic certain to overseas key within the secondary table and each non-key characteristic certain to columns from the secondary table.
Question 4. What Is Factless Fact Table?
Answer:
This could be very crucial interview query. The “Factless Fact Table” is a desk which is just like Fact Table except for having any degree; I imply that this table simply has the links to the dimensions. These tables permit you to song activities; certainly they may be for recording occasions.
Factless truth tables are used for tracking a procedure or collecting stats. They are referred to as so because, the fact desk does now not have aggregatable numeric values or information. They are mere key values almost about the dimensions from which the stats may be gathered
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Question 5. What Is Fact Table?
Answer:
A fact desk incorporates the basic facts which you want to summarize. The table that shops the distinctive fee for degree is known as truth table. In simple and first-rate we can outline as “The table which contains METRICS” that are used to examine the enterprise.
It consists of 2 sections:
Foregine key to the dimesion
measures/statistics(a numerical fee that used to screen enterprise interest)
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Question 6. What Is Dimension Table?
Answer:
A size table contains hierarchical facts through which you’d want to summarize. A dimension table carries unique enterprise statistics, a measurement desk that incorporates the unique name of each member of the size. The name of the measurement member is referred to as an “characteristic”
The key attribute within the dimension should include a unique price for each member of the size. This key characteristic is called “primary key column”
The primary key column of every size desk corresponding to the one of the key column in any associated fact table.
Question: 7. How Will You Add A New Column To An Existing Table In Data Source View?
Answer:
By using named calculations we are able to add a brand new column to an present desk in the statistics supply view.
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Question 8. Why We Need Named Queries?
Answer:
A named query is used to join more than one tables, to do away with useless columns from a desk of a database. You can gain the same in database the usage of Views but this Named Queries can be the great wager whe you don’t have get right of entry to to create Views in database.
Question: 9. What Is Named Query?
Answer:
Named query in DSV is similar to View in Database. This is used to create Virtual table in DSV with a view to not impact the underlying database. Named question is mainly used to merge the two or greater desk in the datasource view or to filter columns of a desk.
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Question 10. What Is Data Source View Or Dsv?
Answer:
A statistics supply view is a continual set of tables from a records supply that supply the facts for a particular dice. BIDS additionally includes a wizard for creating records supply views, which you may invoke by proper-clicking at the Data Source Views folder in Solution Explorer.
Datasource view is the logical view of the statistics within the statistics source.
Data supply view is the only issue a cube can see.
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Question eleven. What Is Named Calculation?
Answer:
A named calculation is a SQL expression represented as a calculated column. This expression seems and behaves as a column within the table. A named calculation lets you amplify the relational schema of current tables or perspectives in a information source view without modifying the tables or views in the underlying facts source.
Named calculation is used to create a new column inside the DSV using hard coded values or by way of the usage of present columns or maybe with each.
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Question 12. What Is A Data Source Or Ds?
Answer:
The records supply is the Physical Connection information that analysis carrier makes use of to connect to the database that host the facts. The statistics supply includes the connection string which specifies the server and the database web hosting the statistics as well as any essential authentication credentials.
SQL Server 2000 Interview Questions
Question thirteen. Explain The Flow Of Creating A Cube?
Answer:
Steps to create a dice in ssas:
Create a facts supply.
Create a datasource view.
Create Dimensions
Create a cube.
Deploy and Process the dice.
Question 14. What Are The Difference Between Data Mart And Data Warehouse?
Answer:
Datawarehouse is whole records in which as Data mart is Subset of the identical.
Ex: All the company facts can also related to finance branch, HR, banking dept are stored in statistics warehouse in which as in information mart most effective finance statistics or HR branch records will be stored. So facts warehouse is a collection of different statistics marts.
Question: 15. What Is Data Mart?
Answer:
A statistics mart is a subset of an organizational statistics store, generally oriented to a specific motive or fundamental statistics issue that may be allotted to guide business desires. Data marts are analytical statistics shops designed to focus on particular enterprise functions for a particular network within an business enterprise.
Data marts are often derived from subsets of facts in a facts warehouse, although inside the backside-up data warehouse layout technique the records warehouse is made out of the union of organizational statistics marts.
They are three styles of statistics mart they are:
Dependent
Independent
Logical facts mart
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Question sixteen. What Is Data Warehouse In Short Dwh?
Answer:
The facts warehouse is an informational environment that:
Provides an included and overall view of the agency
Makes the organisation’s modern-day and ancient statistics without difficulty to be had for decision making
Makes choice-help transactions feasible without hindering operational structures
Renders the business enterprise’s records consistent
Presents a bendy and interactive source of strategic records
Question 17. What Is The Difference Between Ssas 2005 And Ssas2008?
Answer:
In 2005 its not viable to create an empty dice but in 2008 we will create an empty cube.
A new characteristic in Analysis Services 2008 is the Attribute Relationships tab within the Dimension Designer . To put in force characteristic dating is complex in ssas 2005
we are able to create ONLY 2000 partitions in step with Measure Group in ssas 2005 and the same limit of walls is removed in ssas 2008.
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Question 18. How You Provide Security To Cube?
Answer:
By defining roles we provide protection to cubes. Using roles we are able to restrict users from having access to limited facts.
Procedure as follows:
Define Role
Set Permission
Add appropriate Users to the function
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Question 19. What Is Amo?
Answer:
The complete form of AMO is Analysis Management Objects. This is used to create or alter cubes from .NET code.
Question: 20. After Creating The Cube, If We Added A New Column To The Oltp Table Then How You Add This New Attribute To The Cube?
Answer:
Just open the datasourceview and on right click on we find the choice REFRESH. Click the REFRESH then it will upload new attributes to the desk which can be introduced to Cube.
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Question 21. What Is A Cube?
Answer:
The primary unit of garage and analysis in Analysis Services is the dice. A cube is a set of facts that’s been aggregated to allow queries to return records speedy.
For example, a cube of order statistics is probably aggregated through time period and through name, making the cube rapid while you ask questions concerning orders by means of week or orders by title.
Question: 22. What Are The Types Of Processing And Explain Each?
Answer:
They are 6 styles of processing in ssas ,they’re
Process Full
Process Data
Process Index
Process Incremental
Process Structure
UnProcess
Question 23. What Is The Maximum Size Of A Dimension?
Answer:
The maximum length of the dimension is 4 gb.
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Question 24. What Is Deploy, Process And Build?
Answer:
Bulid: Verifies the mission documents and create several neighborhood files.
Deploy: Deploy the shape of the dice(Skeleton) to the server.
Process: Read the statistics from the source and build the scale and dice systems
SQL Server 2008 Interview Questions
Question 25. What Is Perspective, Have You Ever Created Perspective?
Answer:
Perspectives are a manner to lessen the complexity of cubes by using hidden elements like degree agencies, measures, dimensions, hierarchies etc. It’s nothing however reducing of a dice, for ex we are having retail and medical institution records and stop person is subscribed to look most effective health center information, then we are able to create angle according to it.
Question: 26. What Are Aggregations And Its Use?
Answer:
Aggregations provide performance upgrades by permitting Microsoft SQL Server Analysis Services (SSAS) to retrieve pre-calculated totals directly from dice garage rather of getting to recalculate records from an underlying facts supply for each query. To layout those aggregations, you could use the Aggregation Design Wizard.
This wizard courses you thru the following steps:
Selecting trendy or custom settings for the garage and caching options of a partition, degree group, or dice.
Providing estimated or actual counts for items referenced by means of the partition, measure group, or cube.
Specifying aggregation options and bounds to optimize the storage and query overall performance added by means of designed aggregations.
Saving and optionally processing the partition, measure group, or dice to generate the defined aggregations.
After you operate the Aggregation Design Wizard, you could use the Usage-Based Optimization Wizard to layout aggregations based totally on the usage patterns of the enterprise customers and consumer packages that question the dice.
Question 27. What Is The Minimum And Maximum Number Of Partitions Required For A Measure Group?
Answer:
In 2005 a MAX of 2000 partitions may be created per degree organization and that restrict is lifted in later variations.
In any version the MINIMUM is ONE Partition according to degree group.
SQL Server 2005 Interview Questions
Question 28. What Is Partition, How Will You Implement It?
Answer:
You can use the Partition Wizard to outline partitions for a measure organization in a dice. By default, a unmarried partition is defined for every measure institution in a dice. Access and processing overall performance, however, can degrade for large partitions. By growing more than one walls, every containing a part of the information for a degree group, you can enhance the get entry to and processing overall performance for that degree group.
Question: 29. What Are Actions, How Many Types Of Actions Are There, Explain With Example?
Answer:
Actions are powerful manner of extending the cost of SSAS cubes for the quit user. They can click on a dice or part of a dice to begin an application with the selected object as a parameter, or to retrieve records about the selected object.
One of the objects supported with the aid of a SQL Server Analysis Services dice is the motion. An action is an event that a consumer can provoke whilst accessing dice data. The occasion can take a number of paperwork. For example, a consumer is probably capable of view a Reporting Services file, open a Web web page, or drill through to certain records related to the dice facts
Analysis Services helps three styles of moves..
Report movement: Report motion Returns a Reporting Services record that is associated with the cube records on which the action is based.
Drill via: Drillthrough Returns a result set that provides specified data associated with the dice records on which the motion is based totally.
Standard: Standard has 5 action subtypes which can be based totally on the required dice records.
Dataset: Returns a multidimensional dataset.
Proprietary: Returns a string that can be interpreted via a customer utility.
Rowset: Returns a tabular rowset.
Statement: Returns a command string that can be run via a patron utility.
URL: Returns a URL that can be opened through a patron utility, normally a browser.
Question 30. What Are Kpis And What Is Its Use?
Answer:
In Analysis Services, a KPI is a set of calculations which are associated with a measure institution in a cube that are used to assess business success. We use KPI to peer the business at the specific point, that is represents with some graphical gadgets inclusive of traffic alerts,ganze and many others
Question: 31. What Are Calculated Members And What Is Its Use?
Answer:
Calculations are item inside the dice which might be eveluated at runtime
Calculated individuals: You can create custom designed measures or size contributors, called calculated contributors, with the aid of combining cube statistics, arithmetic operators, numbers, and/or features.
Example: You can create a calculated member known as Marks that converts dollars to marks by means of multiplying an present dollar measure by a conversion charge. Marks can then be displayed to cease users in a separate row or column. Calculated member definitions are saved, but their values exist best in reminiscence. In the previous instance, values in marks are exhibited to quit customers however aren’t stored as dice information.
Question: 32. What Is Regular Type, No Relation Type, Fact Type, Referenced Type, Many-to-many Type With Example?
Answer:
No dating: The size and measure group are not related.
Regular: The dimension desk is joined at once to the fact table.
Referenced: The size table is joined to an intermediate desk, which in turn,is joined to the reality table.
Many to many:The size desk is to an intermediate fact table,the intermediate fact desk is joined , in flip, to an intermediate measurement desk to which the reality table is joined.
Data mining:The target measurement is based on a mining model built from the source dimension. The supply size ought to also be protected in the cube.
Fact table: The measurement table is the fact table.
Question 33. How Many Types Of Relations Are There Between Dimension And Measure Group?
Answer:
They are six relation among the size and degree organization, they’re
No Relationship
Regular
Refernce
Many to Many
Data Mining
Fact
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Question 34. What Is Attribute?
Answer:
An characteristic is a specification that defines a property of an object, detail, or report. It may also talk over with or set the specific fee for a given instance of such.
Question: 35. What Is Surrogate Key?
Answer:
A surrogate key’s the SQL generated key which acts like an change primary key for the desk in database, Data warehouses typically use a surrogate key to uniquely pick out an entity. A surrogate isn’t generated with the aid of the consumer but with the aid of the system. A number one difference between a number one key and surrogate key in few databases is that primarykey uniquely identifies a document whilst a Surrogatekey uniquely identifies an entity.
Ex: An employee may be recruited earlier than the year 2000 while another worker with the identical name can be recruited after the 12 months 2000. Here, the primary key will uniquely pick out the report at the same time as the surrogate key will be generated with the aid of the system (say a serial number) for the reason that SK is NOT derived from the records.
Question: 36. What Is Measure Group, Measure?
Answer:
Measure businesses : These degree businesses can contain special dimensions and be at exceptional granularity however so long as you model your dice efficiently, your customers could be capable of use measures from every of those measure businesses of their queries without difficulty and without annoying approximately the underlying complexity.
Creating multiple measure organizations : To create a brand new measure institution in the Cube Editor, go to the Cube Structure tab and proper-click at the cube call inside the Measures pane and choose ‘New Measure Group’. You’ll then need to select the reality table to create the degree institution from after which the new degree group might be created; any columns that aren’t used as foreign key columns within the DSV will robotically be created as measures, and also you’ll also get an extra measure of aggregation kind Count. It’s a great concept to delete any measures you are not going to apply at this level.
Measures : Measures are the numeric values that our users want to mixture, slice, cube and in any other case examine, and as a result, it’s critical to ensure they behave the manner we need them to. One of the essential reasons for the usage of Analysis Services is that, in contrast to a relational database it permits us to build into our dice design enterprise policies approximately measures: how they ought to be formatted, how they ought to mixture up, how they interact with unique dimensions and so forth.
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Question 37. What Is Role Playing Dimension With Two Examples?
Answer:
Role play dimensions: We already discussed about this. This is nothing but CONFIRMED Dimensions. A dimension can play specific role in a reality desk you could apprehend a roleplay size while there are a couple of columns in a reality desk that every have foreign keys to the same size desk.
Ex1: There are three dimension keys within the factinternalsales,factresellersales tables which all discuss with the dimtime desk,the same time measurement is used to music sales by that incorporate both of these fact table,the corresponding position-playing size are routinely introduced to the cube.
Ex2 : In retail banking, for checking account dice we should have transaction date dimension and powerful date measurement. Both dimensions have date, month, sector and 12 months attributes. The formats of attributes are the same on both dimensions, for instance the date characteristic is in ‘dd-mm-yyyy’ format. Both dimensions have individuals from 1993 to 2010.
Question: 38. What Is Scd (slowly Changing Dimension)?
Answer:
Slowly converting dimensions (SCD) determine how the historic adjustments within the size tables are handled. Implementing the SCD mechanism permits customers to recognise to which class an item belonged to in any given date.
Question: 39. What Are Types Of Scd?
Answer:
It is a concept of STORING Historical Changes and whilst ever an IT man finds a new manner to store then a new Type will come into picture. Basically there are 3 varieties of SCD they are given below
SCD type1
SCD type2
SCD type3
Question 40. How Will You Add A Dimension To Cube?
Answer:
To add a dimension to a dice comply with these steps.
In Solution Explorer, right-click on the cube, and then click View Designer.
In the Design tab for the dice, click the Dimension Usage tab.
Either click on the Add Cube Dimension button, or right-click anywhere at the work floor and then click on Add Cube Dimension.
In the Add Cube Dimension dialog box, use one of the following steps:
To add an current size, pick the dimension, and then click OK.
To create a brand new dimension to add to the dice, click on New dimension, after which follow the stairs within the Dimension Wizard.
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Question forty one. What Is Database Dimension?
Answer:
All the scale which might be created using NEW DIMENSION Wizard are database dimensions. In different phrases, the scale which can be at Database level are called Database Dimensions.
Question: 42. What Is Cube Dimension?
Answer:
A dice size is an instance of a database measurement within a cube is called as dice size. A database dimension may be used in more than one cubes, and a couple of cube dimensions can be based totally on a unmarried database size
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Question forty three. Difference Between Database Dimension And Cube Dimension?
Answer:
The Database dimension has simplest Name and ID properties, whereas a Cube size has numerous more homes.
Database measurement is created one in which as Cube size is referenced from database dimension.
Database dimension exists only once. Where as Cube dimensions can be created multiple the usage of ROLE PLAYING Dimensions concept.
Question 44. What Is Molap And Its Advantage?
Answer:
MOLAP (Multi dimensional Online Analytical Processing) : MOLAP is the most used garage type. Its designed to offer most question overall performance to the users. The information and aggregations are stored in a multidimensional format, compressed and optimized for performance. This is each right and terrible. When a cube with MOLAP garage is processed, the records is pulled from the relational database, the aggregations are executed, and the facts is stored within the AS database. The records within the cube will refresh handiest whilst the dice is processed, so latency is excessive.
Advantages:
Since the information is stored on the OLAP server in optimized layout, queries (even complicated calculations) are faster than ROLAP.
The facts is compressed so it takes up less area.
And due to the fact the data is saved at the OLAP server, you don’t need to keep the relationship to the relational database.
Cube browsing is quickest the usage of MOLAP.
Question 45. What Is Rolap And Its Advantage?
Answer:
ROLAP (Relational Online Analytical Processing) : ROLAP does not have the high latency downside of MOLAP. With ROLAP, the records and aggregations are stored in relational layout. This method that there will be zero latency among the relational source database and the dice.
Disadvantage of this mode is the overall performance, this kind offers the poorest question overall performance due to the fact no objects gain from multi dimensional storage.
Advantages:
Since the facts is saved within the relational database in place of at the OLAP server, you could view the information in almost real time.
Also, since the data is stored within the relational database, it allows for a great deal large quantities of information, that may suggest higher scalability.
Low latency.
Question forty six. What Is Holap And Its Advantage?
Answer:
Hybrid Online Analytical Processing (HOLAP): HOLAP is a combination of MOLAP and ROLAP. HOLAP stores the detail facts within the relational database but shops the aggregations in multidimensional layout. Because of this, the aggregations will want to be processed while changes are arise. With HOLAP you type of have medium query performance: now not as slow as ROLAP, however no longer as rapid as MOLAP. If, but, you were best querying aggregated records or using a cached query, query performance would be much like MOLAP. But while you want to get that detail statistics, overall performance is toward ROLAP.
Advantages:
HOLAP is satisfactory used whilst large quantities of aggregations are queried often with little element statistics, providing excessive overall performance and lower garage necessities.
Cubes are smaller than MOLAP for the reason that element information is kept inside the relational database.
Processing time is much less than MOLAP due to the fact that only aggregations are saved in multidimensional layout.
Low latency since processing takes region whilst changes arise and element statistics is stored in the relational database.
Question 47. What Are Translations And Its Use?
Answer:
Translation: The translation function in evaluation provider lets in you to display caption and attributes names that correspond to a specific language. It facilitates in supplying GLOBALIZATION to the Cube.
Question: 48. What Is Hierarchy, What Are Its Types And Difference Between Them?
Answer:
A hierarchy is a completely critical part of any OLAP engine and lets in customers to drill down from summary tiers hierarchies represent the manner person assume to explore statistics at extra special level
hierarchies is made of multipule ranges growing the structure primarily based on cease person necessities.
->years->sector->month->week ,are all the tiers of calender hierarchy
They are 2 types of hierarchies they are
Natural hierarchy
Unnatural hierarchy
Natural hierarchy: This approach that the attributes are intuitively related to one another. There is a clear dating from the top of the hierarchy to the bottom.
Example: An instance of this would be date: year, zone and month observe from each other, and in part, outline every different.
Unnatural hierarchy: This method that the attributes aren’t certainly related.
Example: An instance of this might be geography; we may additionally have country -> kingdom -> metropolis, however it isn’t always clean wherein Province may sit down.
Question forty nine. What Is Attribute Hierarchy?
Answer:
An attribute hierarchy is created for every attribute in a dimension, and each hierarchy is available for dimensioning truth records. This hierarchy includes an “All” stage and a detail degree containing all contributors of the hierarchy.
You could prepare attributes into person-defined hierarchies to offer navigation paths in a cube. Under sure situations, you may need to disable or disguise a few attributes and their hierarchies.
Question: 50. What Is Use Of Attributehierarchydisplayfolder Property ?
Answer:
AttributeHierarchyDisplayFolder: Identifies the folder wherein to show the associated characteristic hierarchy to stop users. For example if I set the assets fee as “Test” to all the Attributes of a size then a folder with the call “Test” may be created and all the Attributes can be positioned into the equal.
Question: fifty one. What Is Use Of Attributehierarchyenabled?
Answer:
AttributeHierarchyEnabled: Determines whether an characteristic hierarchy is generated through Analysis Services for the characteristic. If the characteristic hierarchy isn’t enabled, the characteristic can’t be utilized in a consumer-described hierarchy and the attribute hierarchy cannot be referenced in Multidimensional Expressions (MDX) statements.
Question: fifty two. What Is Use Of Attribute Hierarchy Optimized State?
Answer:
Attribute Hierarchy Optimized State:
Determines the level of optimization implemented to the characteristic hierarchy. By default, an characteristic hierarchy is FullyOptimized, because of this that Analysis Services builds indexes for the attribute hierarchy to improve query overall performance. The different alternative, NotOptimized, method that no indexes are constructed for the characteristic hierarchy. Using NotOptimized is beneficial if the characteristic hierarchy is used for functions apart from querying, due to the fact no extra indexes are built for the characteristic. Other makes use of for an characteristic hierarchy may be helping to reserve some other attribute.
Question: 53. What Is Use Of Attribute Hierarchy Ordered ?
Answer:
Attribute Hierarchy Ordered: Determines whether or not the associated attribute hierarchy is ordered. The default fee is True. However, if an characteristic hierarchy will not be used for querying, you could keep processing time by means of changing the price of this assets to False.
Question: 54. What Is The Use Of Attributehierarchyvisible ?
Answer:
AttributeHierarchyVisible : Determines whether or not the characteristic hierarchy is visible to customer applications. The default fee is True. However, if an characteristic hierarchy will no longer be used for querying, you can save processing time by using changing the cost of this property to False.
Question: 55. What Are Types Of Storage Modes?
Answer:
There are 3 widespread storage modes in OLAP applications
MOLAP
ROLAP
HOLAP
Question 56. What Are The Types Of Database Schema?
Answer:
They are three varieties of database schema they are
Star
Snowflake
Starflake
Question 57. What Is Star, Snowflake And Star Flake Schema?
Answer:
Star schema: In celebrity schema truth table may be immediately connected with all size tables. The famous person schema’s dimensions are denormalized with each dimension being represented by using a unmarried desk. In a star schema a central reality desk connects a number of character measurement tables.
Snowflake: The snowflake schema is an extension of the star schema, where each factor of the megastar explodes into greater factors. In a star schema, each measurement is represented with the aid of a single dimensional desk, while in a snowflake schema, that dimensional table is normalized into multiple research tables, each representing a stage in the dimensional hierarchy. In snow flake schema truth desk might be connected directly in addition to there will be some intermediate dimension tables between fact and size tables.
Star flake: A hybrid shape that incorporates a combination of celebrity(denormalized) and snowflake(normalized) schema’s.
Question: fifty eight. How Will You Hide An Attribute?
Answer:
We can conceal the attribute by means of selecting “AttributeHierarchyVisible = False” in properties of the attribute.
Question: fifty nine. How Will You Make An Attribute Not Process?
Answer:
By choosing “ AttributeHierarchyEnabled = False”, we are able to make an characteristic not in technique.
Question: 60. What Is Use Of Isaggregatable Property?
Answer:
In Analysis Service we commonly see all size has All member. This is due to IsAggregatable assets of the characteristic. You can set its value to false, so that it will no longer display All member. Its default member for that characteristic. If you hide this member than you will should set different attribute fee to default member else it’s going to pick a few fee as default and this can create confusion in browsing facts if someone isn’t recognised to alternate in default member.
Question: sixty one. What Are Key, Name And Value Columns Of An Attribute?
Answer:
Key column of any attribute: Contains the column or columns that represent the key for the attribute, which is the column within the underlying relational table inside the information source view to which the characteristic is sure. The fee of this column for every member is displayed to users unless a price is certain for the NameColumn belongings.
Name column of an characteristic: Identifies the column that offers the call of the attribute that is exhibited to users, rather than the fee in the key column for the characteristic. This column is used when the key column cost for an characteristic member is cryptic or not otherwise useful to the person, or when the important thing column is primarily based on a composite key. The NameColumn property is not utilized in figure-child hierarchies; alternatively, the NameColumn belongings for infant contributors is used because the member names in a discern-toddler hierarchy.
Value columns of an characteristic: Identifies the column that offers the price of the characteristic. If the NameColumn detail of the attribute is precise, the equal DataItem values are used as default values for the ValueColumn element. If the NameColumn detail of the characteristic isn’t specific and the KeyColumns series of the characteristic consists of a single KeyColumn element representing a key column with a string facts kind, the identical DataItem values are used as default values for the ValueColumn detail.
Question: 62. What Are The Difficulties Faced In Cube Development?
Answer:
Giving attribute relationships
Calculations
Giving size utilization (many to many dating)
Analyzing the necessities
Question 63. What Is Impersonation? What Are The Different Impersonation Options Available In Ssas?
Answer:
Impersonation permits SSAS to anticipate the identity/protection context of the client utility that is utilized by SSAS to perform the server side statistics operations like records get admission to, processing and so forth. As a part of impersonation, the following options are to be had in SSAS:
Use a specific Windows user name and password: This option helps you to to specify Windows account credentials on the way to be used by SSAS to carry out operations like supply statistics access, processing and many others.
Use the provider account: When this option is selected, SSAS uses the credentials of the service account below which the Analysis Services provider is configured/walking for supply statistics get right of entry to, processing etc.
Use the credentials of the contemporary person: When this feature is set, SSAS uses the credentials of the contemporary consumer for acting operations like DMX Open Queries, Local cubes etc. This choice can’t be used for performing server aspect operations like supply records get admission to, processing and many others.
Inherit: This option let’s the SSAS server determine which impersonation mode is appropriate for each form of operation. When this selection is set, with the aid of default SSAS will use the carrier account for operations like processing and the credentials of the cutting-edge person for operations like Local cubes, querying the statistics mining fashions, and so on…
Question 64. What Is A Data Source? What Are The Different Data Sources Supported By Ssas?
Answer:
A Data Source contains the connection facts used by SSAS to connect with the underlying database to load the data into SSAS for the duration of processing. A Data Source frequently contains the subsequent statistics (aside from numerous different residences like Query timeout, Isolation and so forth.):
Provider
Server Name
Database Name
Impersonation Information
• SSAS Supports both .Net and OLE DB Providers. Following are a number of the principal sources supported with the aid of SSAS: SQL Server, MS Access, Oracle, Teradata, IBM DB2, and other relational databases with the right OLE DB provider.
Question: sixty five. What Is Sql Server Analysis Services (ssas)?
Answer:
SQL Server Analysis Services (SSAS) is the On-Line Analytical Processing (OLAP) Component of SQL Server. SSAS permits you to construct multidimensional structures known as Cubes to pre-calculate and shop complicated aggregations, and also to build mining models to perform facts analysis to become aware of precious records like traits, styles, relationships etc. Within the records using Data Mining capabilities of SSAS, which in any other case could be clearly hard to determine with out Data Mining abilties.
SSAS comes bundled with SQL Server and you get to select whether or not or now not to put in this issue as part of the SQL Server Installation.
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