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Exam Objectives

Exam Objectives

The exam objectives are broken up into five different categories. The 70-467 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 70-467 as stated by Microsoft are as follows:

Plan Business Intelligence (BI) Infrastructure (15%)

  • Plan for performance.
  • This objective may include but is not limited to: 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 Unified Dimension Model (UDM) and data warehouse (DWH) design; analyze and optimize performances of Multidimensional Expression (MDX) and Data Analysis Expression (DAX) queries; optimize queries for huge data sets; understand the difference between partitioning for load performance vs. query performance in SSAS; appropriately index a fact table; optimize Analysis Services cubes in UDM; create aggregations using Usage-Based Optimizations

  • Plan for scalability.
  • This objective may include but is not limited to: Multidimensional OLAP (MOLAP); Relational OLAP (ROLAP); Hybrid OLAP (HOLAP)

  • Plan and manage upgrades.
  • This objective may include but is not limited to: plan change management for a BI solution

  • Maintain server health.
  • This objective may include but is not limited to: design an automation strategy

Design BI Infrastructure (16%)

  • Design a security strategy.
  • This objective may include but is not limited to: configure security and impersonation between database, analysis services, and front end; implement Dynamic Dimension Security within a cube; configure security for an extranet environment; configure Kerberos security; plan and build secure solutions end to end; design security roles for calculated measures; understand the tradeoffs between regular SSAS security and dynamic security; plan and implement security requirements of a BI solution

  • Design a SQL partitioning strategy.
  • This objective may include but is not limited to: choose a partitioning strategy for the data warehouse and cube; implement a parallel load to fact tables by using partition switching; use data compression in fact tables

  • Design a backup strategy.
  • This objective may include but is not limited to: design a high availability (HA) and disaster recovery strategy

  • Design a logging and auditing strategy.
  • This objective may include but is not limited to: design a new SSIS logging infrastructure (for example, information available through the catalog views); validate that data is balancing and reconciling correctly

Design a Reporting Solution (24%)

  • Design a Reporting Services dataset.
  • 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

  • Manage Microsoft Excel Services/Reporting for SharePoint.
  • This objective may include but is not limited to: configure data refresh schedules for PowerPivot published to SharePoint; publish BI information to SharePoint; use SharePoint to accomplish BI administrative tasks

  • Design a data acquisition strategy.
  • This objective may include but is not limited to: 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; which 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.
  • This objective may include but is not limited to: native mode

  • Design BI reporting solution architecture.
  • 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; identify when to use Reporting Services, Report Builder, or Crescent; design and implement context transfer when interlinking all types of reports (Reporting Services, Report Builder, Crescent, Excel, PowerPivot); implement BI tools for reporting in SharePoint (Excel Services vs. Performance Point vs. Reporting Services); select a subscription strategy

Design BI Data Models (34%)

  • Design the data warehouse.
  • This objective may include but is not limited to: 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 the facilities available in SQL Server to design, implement, and maintain a data warehouse including: partitioning, slowly changing dimensions (SCD), change data capture (CDC), and Clustered Index Views; implement a many-to-many relationship in an OLAP cube; design a data mart/warehouse in reverse from an Analysis Services cube; use rowstamp in the data warehouse; choose between performing aggregation operations in the SSIS pipeline or the relational engine; select surround architecture

  • Design a schema.
  • This objective may include but is not limited to: multidimensional modeling starting from a star schema; relational modeling for a data mart; choose or create a topology

  • Design cube architecture.
  • This objective may include but is not limited to: produce efficient aggregated cubes; partition cubes and build aggregation strategies for the separate partitions; design a data model; choose a partitioning strategy for the data warehouse and cube; design the data file layout for a data warehouse for maximum performance; given a requirement, identify the aggregation method that should be selected for a measure in a MOLAP cube; design cube aggregations to maintain a balance between storage and performance; performance tune a MOLAP cube using aggregations; design a data source view; cube drill-through and write-back actions

  • Design fact tables.
  • This objective may include but is not limited to: design a data warehouse that supports many-to-many dimensions with factless fact tables

  • Design BI semantic models.
  • This objective may include but is not limited to: plan for a multidimensional cube; write a UDM model with many-to-many relationships; choose between UDM and BISM depending on the type of data and workload

  • Design and create MDX calculations.
  • This objective may include but is not limited to: MDX authoring; identify the structures of MDX and the common functions (including tuples, sets, topcount, and SCOPE); identify which MDX statement would return the required result; implement a custom MDX or logical solution for a pre-prepared case task

Design an ETL Solution (11%)

  • Design SSIS package execution.
  • This objective may include but is not limited to: use the new project deployment model; pass values at execution time; share parameters between packages

  • Plan to deploy SSIS solutions.
  • This objective may include but is not limited to: deploy the package to another server with different security requirements; secure Integration Services packages that are deployed at the file system; understand how SSIS packages/projects interact with environments; choose between performing aggregation operations in the SSIS pipeline or the relational engine

  • Design package configurations for SSIS packages.
  • This objective may include but is not limited to: avoid repeating Configuration Information entered in SSIS packages; use configuration files

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