Exam Objectives
The exam objectives are broken up into five different categories. The 70-452 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.
The objectives for Exam 70-452 as stated by Microsoft are as follows:
Designing and Managing Reports (20 percent)
- Design report architecture.
- Design a data acquisition strategy.
- Define a report parameter strategy.
- Design a report layout.
- Design reports by using Report Builder.
- Manage a report environment.
This objective may include but is not limited to: linked reports, drill-down reports, drill-through reports, migration strategies, access report services API, sub reports, Code-Behind strategies.
This objective may include but is not limited to: data query parameters, creating appropriate SQL queries for an application (MDX queries), managing data rights and security, extracting data from Analysis Services, balancing query-based processing vs. filter-based processing, managing data sets through the use of stored procedures.
This objective may include but is not limited to: report cache parameters, expressions, Code-Behind.
This objective may include but is not limited to: selecting report components (crosstab report, TABLIX, design chart), report templates (Report Definition Language), Report Designer, generating report template RDL, adding third-party controls, Visual Studio Report and Development platform.
This objective may include but is not limited to: designing a Report Builder model, using Report Builder templates.
This objective may include but is not limited to: specifying users and roles, subscriptions strategy, designing data sources, designing a deployment plan for completed reports, integrating Microsoft Office SharePoint Server 2007 or Microsoft Windows SharePoint Services 3.0.
Designing Data Mining Models (10 percent)
- Design a mining model and structure.
- Design strategies for staging data for mining.
- Select a strategy for visualizing data mining results.
- Select data mining algorithms.
- Refine testing models.
This objective may include but is not limited to: assigning a data source, specifying filter properties, reconciling heterogeneous data sources, selecting a refresh strategy.
This objective may include but is not limited to: selecting a method for cleaning data (closed-loop process), specifying partitioning of data into testing and training sets.
This objective may include but is not limited to: DMX queries (drill-through queries, structured and unstructured columns, column aliasing), data mining Microsoft Office Excel add-in, designing a report by using reporting services.
This objective may include but is not limited to: sequence, clustering, time series, neural net, association, classification, decision tree.
This objective may include but is not limited to: applying predictions, analyzing results, performing cross-validation.
Administering a BI Solution (15 percent)
- Maintain server health.
- Select a subscription strategy.
- Manage integration services.
- Design a backup strategy.
- Plan and manage upgrades.
- Plan and manage reporting services configuration.
This objective may include but is not limited to: Resource Governor, performance counters, Analysis Server dynamic management views.)
This objective may include but is not limited to: data-driven rights management.
This objective may include but is not limited to: loading and scheduling an SSIS package to run, SSIS storage solutions, migration of packages.
This objective may include but is not limited to: offsite backup, setting up SSAS backup, Reporting Services backup.
This objective may include but is not limited to: data migration, code migration, data security, parallel systems.
This objective may include but is not limited to: Reporting Services Configuration Manager, SSL management, encryption key management, mail management, Web service interface management, configuration files.
Designing the BI Architecture (21 percent)
- Design integration between data visualization components.
- Design the data warehouse.
- Plan for scalability.
- Plan for performance.
- Manage team development issues.
- Plan the configuration of a primary data source.
- Design a security strategy.
This objective may include but is not limited to: MOSS, SSRS, SSAS, designing Excel PivotTable reports, application architecture (Microsoft ASP.NET, Web Service, MicrosoftReportViewer Windows Forms control), Windows Mobile, other data visualization tools.
This objective may include but is not limited to: datamarts, integrating legacy data, creating a dimensional model (star schema, snowflake, matrix bridge, conformed dimensions), utilizing upsert in design.
This objective may include but is not limited to: selecting the appropriate edition of SQL server, selecting the right hardware topology (service distribution), designing the caching strategy (report snapshots, on-demand reports, on-demand-from-cache reports), managing historical data (report history, archiving), selecting the appropriate service host, designing resource utilization of the SSIS package, Read-Only Analysis Server scale-out.
This objective may include but is not limited to: Resource Governor, Proactive Cache, selecting the appropriate storage settings.
This objective may include but is not limited to: integrating Microsoft Visual SourceSafe, TFS, VSTS for database pro, selecting BI entry points (SSIS, reporting services), online or offline cube deployment.)
This objective may include but is not limited to: configuring CDC in a server, insert over DML.
This objective may include but is not limited to: cube, project, reports (security roles, folders, field-level security), encryption keys, SQL services accounts management, encrypted data transmission, SSIS vs. SQL server authentication issues.
Designing and Deploying SSIS Packages (16 percent)
- Design control flow.
- Design data flow.
- Plan the deployment of SSIS packages.
- Design the configuration file for an SSIS package.
- Design a logging and auditing strategy.
This objective may include but is not limited to: tasks and precedence constraints, fuzzy logic control, maintenance tasks, accessing remote data (Web services, FTP), using appropriate variables, data profile.
This objective may include but is not limited to: data transformation, blocking transformations (lookup task), extractions (design constraints), designing the load process, creating a package to load facts, creating an SSIS package to load dimension (SCD2), using capture CDC to locate changed data for SSIS.
This objective may include but is not limited to: design the structure of packages, troubleshoot and design form problems with package, create a package that reports any errors to a log.
This objective may include but is not limited to: enabling configurable values to be consumed by a package.
This objective may include but is not limited to: exception handling, data flow exceptions.
Designing an Analysis Services Database (18 percent)
- Design cube architecture.
- Design for international implementation.
- Design a data source view.
- Design perspectives.
- Design and create business-driven Multidimensional Expressions (MDX) calculations.
- Analyze cube performance.
This objective may include but is not limited to: creating and populating a cube, creating KPIs, actions, calculated members, drillthrough, designing SSAS aggregation, creating and manipulating dimensions (Ragged hierarchy, Flexible, Rigid, Semi-additive, Periodicity, Fact Relationships), selecting a processing mode.
This objective may include but is not limited to: currency conversion, translation, localization.
This objective may include but is not limited to: named queries, denormalization strategy.
This objective may include but is not limited to: enhancing usability through the use of perspectives.
This objective may include but is not limited to: calculated measures, creating a named set in MDX.
This objective may include but is not limited to: optimizing SSAS aggregation, query cube design.