Exam Code: 70-467
Exam Name: Designing Business Intelligence Solutions with Microsoft SQL Server 2012
Questions: 50 Q&As
Updated: 2019-02-08
Price: $ 59 / $ 69

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Plan business intelligence (BI) infrastructure (15%)

  • 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 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 versus query performance in SSAS; appropriately index a fact table; optimize Analysis Services cubes in UDM; create aggregations using Usaged Based Optimizations

  • Plan for scalability

    • Multidimensional OLAP (MOLAP); Relational OLAP (ROLAP); Hybrid OLAP (HOLAP)

  • Plan and manage upgrades

    • Plan change management for a BI solution

  • Maintain server health

    • Design an automation strategy

Design BI infrastructure (16%)

  • Design a security strategy

    • Configure security and impersonation between database, analysis services and frontend; implement Dynamic Dimension Security within a cube; configure security for an extranet environment; configure Kerberos security; skills in authentication mechanisms, ability to 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

    • 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 in fact tables

  • Design a backup strategy

    • Design a High Availability (HA) and Disaster Recovery (DR) trategy; proactively prevent issues

  • 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

Design a reporting solution (24%)

  • Design a Reporting Services dataset

    • 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 versus filter-based processing; managing 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

  • 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; 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

    • Native mode

  • Design BI reporting solution architecture

    • 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/implement context transfer when interlinking all types of reports (RS, RB, Crescent, Excel, PowerPivot); implement BI tools for reporting in SharePoint (Excel Services versus Performance Point versus Reporting Services); select a subscription strategy

Design BI data models (34%)

  • 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 the facilities available in SQL Server to design, implement and maintain a data warehouse (partitioning, slowly changing dimensions (SCD), change data capture (CDC), Clustered Index Views, etc.); 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 (or empty Analysis Services cube that was created referring requirements); 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

    • Multidimensional modeling starting from a star schema; relational modeling for a Data Mart; choose or create a topology

  • Design cube architecture

    • Produce efficient aggregated cubes; 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 for a data warehouse keeping maximum performance in mind; 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

    • Design a data warehouse that supports many to many dimensions with factless fact tables

  • Design BI semantic models

    • Plan for a multidimensional cube; write a UDM model with many to many (this is related to MDX/BISM code, but it is a good example for exercises); choose between UDM and BISM depending on the type of data and workload

  • Design and create MDX calculations

    • MDX authoring; identify the structures of MDX and the common functions (tuples, sets, topcount, SCOPE etc.); identify which MDX statement would return the required result (single result and multiple MDX options provided to test taker); implement a custom MDX or logical solution for a pre-prepared case task

Design an ETL solution (11%)

  • Design SSIS package execution

    • Using new project deployment model; passing values at execution time; share parameters between packages

  • 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; decide between performing aggregation operations in the SSIS pipeline or the relational engine

  • Design package configurations for SSIS packages

    • Avoid repeating configuration information entered in SSIS packages and use configuration files

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