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tunis annonces autotunis annonces chien Tabular Vs OLAP
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Difference between Tabular and OLAP


    Multidimensional and data mining solutions use OLAP modeling constructs (cubes and dimensions) and MOLAP, ROLAP, or HOLAP storage that use disk as the primary data storage for pre-aggregated data.

 

    Tabular solutions use relational modeling constructs such as tables and relationships for modeling data, and the in-memory analytics engine for storing and calculating data. Most, if not all, of the model is stored in RAM and is often much faster than its multidimensional counterpart.

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Summary of supported options

Data Sources Supported (SSAS Multidimensional)

Multidimensional models use data from relational data sources.

Data Sources Supported (SSAS Tabular)

Tabular models support a broader range of data sources, including flat files, data feeds, and data sources that are accessed via ODBC data providers.

 

 

 If the data you need to load is many terabytes in size, a tabular solution might not meet your requirements if available memory cannot accommodate the data.

 

Tabular solutions only support one model.bim file per solution, which means that all work must be done in a single file. Development teams that are accustomed to working with multiple projects in a single solution might need to revise how they work when building a shared tabular solution.

·  Tabular model databases support DAX calculations, DAX queries, and MDX queries.

·  Multidimensional model databases support MDX calculations and MDX queries as well as ASSL.

·  Tabular model databases can use row-level security, using role-based permissions in Analysis Services.

·  Multidimensional model databases can use dimension and cell-level security, using role-based permissions in Analysis Services.

Power View in Office 365 or Power BI sites

Tabular models only.

Power View in SharePoint on-premises

Power View,as a ClickOnce application from SharePoint, can use either an Analysis Services cube or tabular model.

 

Tabular models do not support linked tables. When importing from a PowerPivot workbook that contains a linked table, linked table data is treated as copy\pasted data and stored in the Model.bim file. When viewing properties for a copy\pasted table, the Source Data property is disabled and the Table Properties dialog on the Table menu is disabled

 

 

 

 

 

 

 

·         Experienced SSRS – Report Model Developer

·         Experienced with Microsoft BISM

·         Experienced with Microsoft SSAS – Tabular Model design and development

·         Experience with PowerPivot; PowerView; SSRS Alerts;  PerformancePoint(dashbaord); PowerQuery; SharePoint 2010-2013

 

PerformancePoint Dashboard Designer

PerformancePoint Dashboard Designer is a tool that you can use to create dashboards, scorecards, and reports and publish them to a SharePoint site. Dashboard Designer is part of PerformancePoint Services in Microsoft SharePoint Server 2010.

 

 

Create a BI Semantic Model Connection to a Tabular Model Database

After you set permissions in Analysis Services, you can return to SharePoint and create a BI semantic model connection.

  1. In the library that will contain the BI semantic model connection, click Documents on the SharePoint ribbon.
  2. Click the down arrow on New Document, and select BI Semantic Model Connection File to open the New BI Semantic Model Connection page.
  3. Set both Server and Database properties. If you are unsure of the database name, use SQL Server Management Studio to view a list of the databases that are deployed on the server.

Server name is either the network name of the server, the IP address, or the fully qualified domain name (for example, myserver.mydomain.corp.adventure-works.com). If the server is installed as a named instance, enter the server name in this format: computername\instancename.

Database must be a tabular database that is currently available on the server. Do not specify another BI semantic model connection file, an Office Data Connection (.odc) file, an Analysis Services OLAP database, or a PowerPivot workbook. To get the database name, you can use Management Studio to connect to the server and view the list of available databases. Use the property page of the database to ensure you have the correct name.

  1. Click OK to save the page. At this point, the PowerPivot service application will verify the connection.

 

 

 

Microsoft BISM - Business Intelligence Semantic Model

 

The Microsoft BI Semantic Model or BISM is a new term introduced with the release of SQL Server 2012. It refers to the way Analysis Services and PowerPivot can be used as a semantic layer, on top of other data, for reporting purposes. Rather than being a product on its own, it is a conceptual term to describe the different options you have within Analysis Services 2012.

 

With SQL Server 2012, the ‘Tabular Model' was introduced next to the already existing Multidimensional Model (based on cubes). The Tabular Model however is not build around a cube like the Multidimensional Model, but is based on tables, relationships, in-memory storage (VertiPaq) and columnstore indexes.

 

So actually, the term BISM is more or less the same as the term Analysis Services, which since 2012 has 2 types of models to work with. The Tabular Model that is faster and easier to develop and the Multidimensional Model, which has more advanced options and features.

With the new column store index available in SQL Server 2012, a new possibility appears since the index column store can dramatically improve the performance of a Data Warehouse query on your relational database.

There are some limitations associated with the DirectQuery Mode:

Only DAX is supported which means that it can only be used from Power View (i.e. you cannot browse it from an Excel Pivot Table).

Time calculations are not supported.

Calculated columns are not supported.

 

The lower the cardinality of your column (cardinality means the number of distinct values), the higher the compression rate of your data. This means that you should avoid including data like transaction identifiers, timestamps, etc. in your model to reduce the amount of memory requir

 

The results of DAX queries are never saved within the cache which means that DAX queries will always take the same time to execute.

 

 One important difference is that you can only use one column to establish relationships between tables in a Tabular project whereas in Multi-Dimensional projects you can use multiple columns. This reinforces the need to enable a solid Data Warehouse with appropriate surrogate keys before you start using a Tabular project

 

Some limitations of Tabular compared to Multidimensional:

You cannot define role-playing dimensions (this was especially useful for the Date dimension)

You cannot define Many-to-Many Relationships (there are some workarounds to get the same results but you will have to use very complex DAX formulas)

You cannot define a Parent-Child hierarchy

Custom Rollups are not supported (especially useful when aggregating data following a chart of accounts)

You cannot define Actions (Drill trough, Reporting, etc.)

Write-back is not supported

 

Another very important distinction between both models is that with the Tabular model you can import directly from an existing PowerPivot model. This means that you can easily transfer a personal BI application developed by a Business Analyst to the IT department.

 

Power View provides intuitive ad-hoc reporting for end-users. They can easily create and interact with views of data from data models based on tabular models. Power View is a browser-based Silverlight application launched from SharePoint Server 2010

 

A last remark, native DAX queries can sometimes be faster than MDX queries, which explains why under some circumstances the same report will be faster when executed from Power View instead of another reporting tool (i.e. Microsoft Excel).

 

One difference is worth mentioning: the Tabular model does not support parallel processing of partitions which can have significant impact on the processing time.

 

Tabular Model

Multidimensional Model

Pros

  • More performant than OLAP in majority of the case.
  • Easier to develop than Multidimensional model.
  • Technology for the future.
  • Integration with Power Pivot.
  • Mature Technology.
  • Scalable Technology able to handle very large volume of data.
  • Able to cope with advanced modeling/ computations requirements.

Cons

  • New product so still enhancements to come.
  • Limited to RAM available (= midsized project).
  • Missing some advanced computations available with MDX.
  • Cannot be used with Power View.
  • No major innovations to expect in this product in the future.
  • Higher complexity than Tabular.

 

 

For more information check: https://msdn.microsoft.com/en-us/library/hh212940.aspx

 

 




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