Detailed SQL Server 2008 R2 database SSAS modeling and scaling capabilities _mssql2008

The SSAS modeling tools available in the SQL Server 2008 R2 database include the SQL Servers Management Studio and business Intelligence Studio, so what is the modeling process? Here's what we're going to introduce, and let's take a look at the SQL Server 2008 R2 database modeling tools and key processes, as well as data mining, permissions, and access interfaces.

Modeling tools and key processes

The purpose of the modeling of SSAS is to design multidimensional database objects, including SQL Server Management Studio and business Intelligence Development Studio, which is used to manage analysis Examples of services, SQL Server, Integration Services, and Reporting Services to manage Analysis Services objects (perform backups, processing, and so on), and to use XMLA The script creates the new object directly on the existing analysis Services instance and provides the profiling Server script project. Business Intelligence Development Studio is a development environment based on Visual Studio 2008 for creating and modifying business intelligence solutions. With business Intelligence Development Studio, you can create an Analysis Services project that contains the definitions of Analysis Services objects (cubes, dimensions, and so on).

There are four key steps to using business Intelligence Development Studio Modeling:

(1) Define an analysis Services project.

(2) Configure the Analysis Services project properties.

(3) to generate an analysis Services project.

(4) Deploying an Analysis Services project.

Scalability of the SSAS database, including: Data mining, permissions, and Access interfaces

SSAS provide more advanced features than traditional OLAP platforms. This enables organizations to leverage a solution to meet a variety of analysis requirements, because the solution provides more features than traditional OLAP platforms. In this context, the Unified Dimensional model (the Unified dimension models) plays a central role, providing a rich analysis capability.

The Unified dimension model (Unified dimensional MODEL,UDM) is a new concept for analysis Services, which first emerged with the release of SQL Server 2005. It provides an intermediate logical layer between a physical relational database used as a data source and a proprietary cube and a dimension structure for satisfying user queries. In this way, UDM can be treated as a core part of an OLAP solution. The model also provides rich advanced business intelligence capabilities to provide optimal relational analysis and OLAP analysis, and further enables organizations to leverage unique key performance indicator frameworks (Critical performance metrics framework) and complex predictive analytics capabilities, Easily expand the solution. SSAS are easy to extend not only for solutions, but also for data mining, permissions, and access interfaces, described below:

(1) Data Mining extension

The extension of SASS to data mining is mainly embodied in: providing a set of industry standard data mining algorithms; Through data Mining Designer, you can create, manage, and browse data mining models, and then use them to create predictions; support the data Mining Extensions (DMX) language. Can be used to manage mining models and create complex prediction queries.

These features and tools provide an effective extension of data mining, individual use of a single function or tool, and the combination of these features and tools to discover trends and patterns in data and support data for decisions.

(2) Permission extension

The protection of the SASS logarithm is divided into two levels: instance-level and user-level. The instance level consists of all the physical elements used by the analysis Services instance and must be protected to ensure that only authorized users have access to them. These elements include data folders, applications, and so on. The user level consists of the permissions granted to users that allow users to access information stored in the analysis Services database and prevent users from accessing data that exceeds their privileges, and the user-level permissions are implemented in the following ways:

• Establish user authentication mechanism
• To define user permission permissions for the server role
• Defining OLAP Object-level security
• Defining data Mining Object-level security
• Defining assembly and stored procedure-level security
• Enable or disable instance configuration properties

(3) Access interface extension

In the process of developing reports or data mining using SSAS, the extension of the provider includes OLE DB for Data Mining, adomd.net, profiling Management Objects (AMO), analysis Services scripting languages.

OLE DB for Data Mining extends the Microsoft OLE DB for Data Mining 1.0 specification to add new schema rowsets, add columns to existing schema rowsets, and add language to the Data Mining Extensions (DMX) language for creating and managing mining structures Method.

The Profiling Management Object (AMO) is a complete object library that can be accessed programmatically to enable an application to manage a running Microsoft SQL Server Analysis Services instance. ADOMD. NET is the Microsoft. NET Framework data provider that is used to communicate with Microsoft SQL Server Analysis Services. Adomd.net can use the XML for Analysis protocol to communicate with the profiling data source to transmit and receive SOAP requests and responses that conform to the XML for analysis specification using TCP/IP or HTTP connections.

The Analysis Services Scripting language (Analysis Services script LANGUAGE,ASSL) is the scripting language used by Sass client applications and Analysis Services communications, and is a special XML language, Includes the object definition language and the command language that sends an action command to an analysis Services instance.

About SQL Server 2008 R2 Database SSAS modeling knowledge is introduced here, I hope this introduction can bring you some harvest.