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Executing DBCC for SQL Server Analysis Services 2016

In the upcoming release of SQL Server Analysis Services 2016, one of the new features you’ll see is the ability to perform a database consistency check against your SSAS cubes and Tabular models. Just like in the database engine side of things, DBCC for SSAS checks for corruption across the entire database or individual objects within the database.

The DBCC command is shaped likes the XMLA Process command so there’s not a lot of complexity to it. Below here, you can see the basic syntax for the SSAS DBCC command. Its worthing noting that the syntax of the command will look the same whether you’re running it against an SSAS multidimensional database or Tabular model.

"http://schemas.microsoft.com/analysisservices/2003/engine">
    <Object>
        
        
        
        
    Object>

To run the DBCC command, just open a new MDX query window and use the code seen above. Enter in the IDs of your Database, cube, measure and/or partition.

When you’re running the DBCC command against a Tabular model, there are a couple things I’d like to point out.

In the element for the CubeID, you’ll need to specify the ID of the Model. And in the element for the MeasureGroupID, specify the ID for the table you want to check.

DBCC XMLA command for SSAS

If you want to check the whole database or model for consistency, simply remove the elements the lower elements. For example, if I wanted to check the whole model, I just would leave out the elements for MeasureGroupID and PartitionID.

To find the MeasureGroupID (Table ID) or PartitionID in a Tabular model, just navigate to the Properties for that object.

Find the SSAS Tabular MeasureGroup ID or Table ID

To find the Partition ID in a Tabular model, right click the table and select Partitions. Then highlight the partition you want to check and click the Settings icon.

Find the SSAS Tabular partition ID

If you run SQL Server Profiler against SSAS while executing the DBCC command, you can see the individual checking of the columns, tables, database and more.

SSAS Tabular Profiler trace DBCC

I also ran a trace against my SSAS 2016 OLAP instance to watch each segment of

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Getting Started with Data Quality Services (DQS) 2012

  • 29 March 2012
  • Author: cprice1979
  • Number of views: 13464
  • 0 Comments

Data Quality Services is a new and powerful feature that is available in SQL Server 2012. Called a knowledge-driven data quality product, DQS allows you to build knowledge bases that handle the traditional data quality tasks such as profiling, correction, enrichment, standardization and de-duplication.  In this blog series we will dive into DQS and explore how its numerous features and capabilities can improve and enrich your critical and valuable business data. 

 

DQS Blog Series Index

Part 1: Getting Started with Data Quality Services (DQS) 2012

Part 2: Building Out a Knowledge Base

Part 3: Knowledge Discovery in DQS

Part 4: Data Cleansing in DQS

Part 5 : Building a Matching Policy in DQS

Part 6: Matching Projects in DQS

Part 7: Activity Monitoring, Configuration & Security in DQS

 

Installing the DQS Server and Data Quality Client

Data Quality Services consist of two components: DQS Server and the Data Quality Client. Both of these components are install by the Data Quality Server Installer. 

To install the DQS server and client, select 'Data Quality Server Installer' shortcut from the the Microsoft SQL Server 2012 RC0/Data Quality Services folder on the All Programs menu of the Start button. 

DQS_Install_1 

Once the installer starts, you will be prompted to enter a password for the database master key. This key will be used to encrypt the contents of the DQS databases. 

DQS_Install_2

 The process to install the DQS components may take several minutes. During this process three databases and an out of the box knowledge base is created. The three databases that are created are: 

  • DQS_MAIN - This database contains all the DQS stored procedures, the DQS engine and published knowledge bases
  • DQS_PROJECTS - Contains the data associated with data quality projects created in the Data Quality Client
  • DQS_STAGING_DATA - As the name implies, this is a staging area where you can both copy data to perform DQS operations on it as well as export processed data from. 

DQS_Install_3

 The installation process also creates several DQS server logins  (##MS_dqs_db_owner_login##  and ##MS_dqs_service_login##) and DQS database roles (dqs_administrator, dqs_kb_editor and dqs_kb_operator). To handle DQS initialization, a stored procedure is created in master database. It should also be noted that is the installer can find a Master Data Services database instance on the same service it create a user and map it to the MDS login and then grant administrator access to the DQS_MAIN database. 

DQS_Install_5 

Once the installer finishes, you will be prompted to press any key to exit and the installation is complete. 

Miscellaneous Notes:

  • The Microsoft.Net Framework 4.0 is required to run the Data Quality Client.
  • To login to the Data Quality Client a user must be in one of the DQS roles. If a user is in the sysadmin server role, it is not necessary to add them to the DQS roles.
  • If you are running the client on a separate computer, TCP/IP must be enabled on the instance hosting the DQS server.

First Look at the Data Quality Client

To begin working with DQS open the Data Quality Client from All Programs menu on the Start button. When the application launches you will be prompted to enter the server name of instance which host your DQS server. Before you click 'Connect', note that you have an option to 'Encrypt connection' which will use a SSL connection for the communications between the client and server. 

DQS_Install_6 

Once you are connected you will notice, three distinct areas: Knowledge Base Management, Data Quality Projects and Administration. We will dive deeper into these areas in the next blog post but I just want to cover some of the high level concepts that are important in the DQS world. 

DQS_Install_4     

  • Knowledge Base - collection of data domains
  • Domain - contain domain values and status, domain rules, term-based relations, and reference data. Domains can either be single or composite
  • Knowledge Discovery - analyzes organizational data to build knowledge that can be used in cleansing, matching and profiling
  • Cleansing - Process of using the a knowledge base to propose data corrections
  • Matching Policy - Rules used to perform data de-duplication. These rules can be fine tuned by matching results and profiling that creates additional matching policies.
  • Reference Data - Data that can be used to validate and enrich your data. Reference data providers are available in the Azure Marketplace Data Market or you have the option of connecting directly to your provider.

In the next blog post we put DQS to use by building out a knowledge base with domains and business rules, run through the data discovery process and then build out a matching policy. 

Till next time!! 

Chris

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