Published: June 11, 2012
Languages: English, Chinese (Simplified), French, German, Japanese, Portuguese (Brazil)
Audiences: IT professionals
Technology: Microsoft SQL Server
Credit toward certification: MCP, MCSE
This exam measures your ability to accomplish the technical tasks listed below. The percentages indicate the relative weight of each major topic area on the exam. The higher the percentage, the more questions you are likely to see on that content area on the exam. View video tutorials about the variety of question types on Microsoft exams.
Please note that the questions may test on, but will not be limited to, the topics described in the bulleted text.
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As of February 18, 2016, this exam includes content covering both SQL Server 2012 and 2014. Please note that this exam does not include questions on features or capabilities that are present only in the SQL Server 2012 product. For more information, please download and review this document.
Plan business intelligence (BI) infrastructure (15–20%)
Plan for performance
Optimize batch procedures: extract, transform, load (ETL) in SQL Server Integration Services (SSIS)/SQL and processing phase in Analysis Services; configure Proactive Caching within SQL Server Analysis Services (SSAS) for different scenarios; understand performance consequences of named queries in a data source view; analyze and optimize performance, including Multidimensional Expression (MDX) and Data Analysis Expression (DAX) queries; understand the difference between partitioning for load performance versus query performance in SSAS; appropriately index a fact table; optimize Analysis Services cubes in SQL Server Data Tools; create aggregations
Plan for scalability
Change binding options for partitions; choose the appropriate Multidimensional OLAP (MOLAP), Relational OLAP (ROLAP), and Hybrid OLAP (HOLAP) storage modes
Plan and manage upgrades
Plan change management for a BI solution
Maintain server health
Design an automation strategy
Create and manage a local partition
Partition storage modes and processing
Designing Aggregations (Analysis Services – Multidimensional)
Design BI infrastructure (15–20%)
Design a security strategy
Configure security and impersonation between SQL Server service, analysis services, and front end; implement Dynamic Dimension Security within a cube; configure security for an extranet environment; configure Kerberos security; design authentication mechanisms; design security tests; build secure solutions end to end; design roles for calculated measures; understand the tradeoffs between regular SSAS security and dynamic security
Design a SQL partitioning strategy
Choose the proper partitioning strategy for the data warehouse and cube, implement a parallel load to fact tables by using partition switching, use data compression
Design a high availability and disaster recovery strategy
Design a recovery strategy, back up and restore SSAS databases, back up and restore SSRS databases, move and restore the SSIS Catalog, design an AlwaysON solution
Design a logging and auditing strategy
Design a new SSIS logging infrastructure (for example, information available through the catalog views), validate data is balancing and reconciling correctly
Granting cube access
Connection string properties
Partitioned tables and indexes
Design a reporting solution (20–25%)
Design a Reporting Services dataset
Design appropriate data query parameters, create appropriate SQL queries, create appropriate DAX queries for an application, manage data rights and security, extract data from analysis services by using MDX queries, balance query-based processing versus filter-based processing, manage data sets through the use of stored procedures
Manage Excel Services/reporting for SharePoint
Configure data refresh schedules for PowerPivot published to SharePoint, publish BI info to SharePoint, use SharePoint to accomplish BI administrative tasks, install and configure Power View, publish PowerPivot and Power View to SharePoint
Design a data acquisition strategy
Identify the data sources that need to be used to pull in the data, determine the changes (incremental data) in the data source (time window), identify the relationship and dependencies between the data sources, determine who can access which data, determine what data can be retained for how long (regulatory compliance, data archiving, aging), design a data movement strategy, profile source data
Plan and manage reporting services configuration
Choose the appropriate reporting services requirements (including native mode and SharePoint mode)
Design BI reporting solution architecture
Linked drill-down reports, drill-through reports, and sub reports; design report migration strategies; access report services API; design code-behind strategies; identify when to use Reporting Services (RS), Report Builder (RB), or Power View; design and implement context transfer when interlinking all types of reports (RS, RB, Power View, Excel); implement BI tools for reporting in SharePoint (Excel Services versus PowerView versus Reporting Services); select a subscription strategy; enable Data Alerts; design map visualization
Configure Windows Authentication on the Report Server
Different ways to update data in PowerPivot
Add dataset filters, data region filters, and group filters (Report Builder and SSRS)
Design BI data models (30–35%)
Design the data warehouse
Design a data model that is optimized for reporting; design and build a cube on top; design enterprise data warehouse (EDW) and OLAP cubes; choose between natural keys and surrogate keys when designing the data warehouse; use SQL Server to design, implement, and maintain a data warehouse, including partitioning, slowly changing dimensions (SCD), change data capture (CDC), Index Views, and column store indexes; identify design best practices; implement a many-to-many relationship in an OLAP cube; design a data mart/warehouse in reverse from an Analysis Services cube; implement incremental data load; choose between performing aggregation operations in the SSIS pipeline or the relational engine
Design a schema
Multidimensional modeling starting from a star or snowflake schema, design relational modeling for a Data Mart
Design cube architecture
Partition cubes and build aggregation strategies for the separate partitions; design a data model; choose the proper partitioning strategy for the data warehouse and cube; design the data file layout; identify the aggregation method for a measure in a MOLAP cube; performance tune a MOLAP cube using aggregations; design a data source view; design for cube drill-through and write back actions; choose the correct grain of data to store in a measure group; design analysis services processing by using indexes, indexed views, and order by statements
Design fact tables
Design a data warehouse that supports many to many dimensions with factless fact tables
Design BI semantic models
Plan for a multidimensional cube; support a many-to-many relationship between tables; choose between multidimensional and tabular, depending on the type of data and workload
Design and create MDX calculations
Design MDX queries, identify the structures of MDX and the common functions (tuples, sets, TopCount, SCOPE, VisualTotals, and more), create calculated members in an MDX statement, identify which MDX statement would return the required result, implement a custom MDX or logical solution for a pre-prepared case task
Defining a many-to-many relationship
Define Relationship dialog box (Analysis Services – multidimensional data)
Set aggregation options (Usage-Based Optimization Wizard)
Design an ETL solution (10–15%)
Design SSIS package execution
Use the new project deployment model; pass values at execution time; share parameters between packages; plan for incremental loads versus full loads; optimize execution by using Balanced Data Distributor (BDD); choose optimal processing strategy (including Script transform, flat file incremental loads, and Derived Column transform)
Plan to deploy SSIS solutions
Deploy the package to another server with different security requirements, secure integration services packages that are deployed at the file system, demonstrate awareness of SSIS packages/projects and how they interact with environments (including recoverability), decide between performing aggregation operations in the SSIS pipeline or the relational engine, plan to automate SSIS deployment, plan the administration of the SSIS Catalog database
Design package configurations for SSIS packages
Avoid repeating configuration information entered in SSIS packages, and use configuration files
Data profiling task
Create package configurations
Deployment of projects and packages
You need to create the Sales Reporting shared SSRS data source.
Which SSRS data connection type should you use?
B. Microsoft SQL Server
D. OLE DB
You need to grant appropriate permissions to the SSISOwners SQL Server login.
What should you do?
A. Map the login to the SSISDB database. Assign the user to the ssis_admin role.
B. Map the login to the msdb database. Assign the user to the db_owner role.
C. Map the login to the msdb database. Assign the user to the db_ssisadmin role.
D. Map the login to the SSISDB database. Assign the user to the db_ssisadmin role.
E. Map the login to the SSISDB database. Assign the user to the db_owner role.
F. Map the login to the msdb database. Assign the user to the ssis_admin role.
You need to configure data refresh for the Manufacturing Performance PowerPivot workbook.
What should you do? (Each correct answer presents part of the solution. Choose ail that apply.)
A. Configure the PowerPivot Data Refresh Timer Job to run every 60 minutes.
B. Restore the PowerPivot workbook to an SSAS instance in tabular mode.
C. Script a process command and configure a SQL Server Agent job to execute the command every 60 minutes.
D. Restore the PowerPivot workbook to an SSAS instance in PowerPivot for SharePoint mode.
You need to configure package execution logging to meet the requirements.
What should you do?
A. Configure logging in each ETL package to log the OnError, OnInformation, and Diagnostic events.
B. Set the SSIS catalog’s Server-wide Default Logging Level property to Performance.
C. Set the SSIS catalog’s Server-wide Default Logging Level property to Basic.
D. Set the SSIS catalog’s Server-wide Default Logging Level property to Verbose.
E. Configure logging in each ETL package to log the OnError, OnPreExecute, and OnPostExecute events.