MCSE Business Intelligence

MCSE Business Intelligence

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Microsoft/
$3,995.00
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$3,995.00

MCSE Business Intelligence
Pre-requisite: MCSA Server 2012

Implementing Data Models and Reports with SQL Server 2012 466
Designing business Intelligence Solutions with MS SQL 2012 467

 

A. Implementing Data Models and Reports with SQL Server 2012    466

  • Build a Tabular Data Model (17%)
    • Configure permissions and roles in Business Intelligence Semantic Model (BISM).
      • This objective may include but is not limited to: server roles; SSAS database roles; implement dynamic security (custom security approaches); role-based access; Test security permissions; cell level permissions
    • Implement a tabular data model.
      • This objective may include but is not limited to: define tables; import data; calculated columns; relationships; hierarchies and perspectives; manage visibility of columns and tables; optimize BISM for Crescent; mark a date table; sort a column by another column
    • Implement business logic in a tabular data model.
      • This objective may include but is not limited to: measures and KPIs; DAX; relationship navigation; time intelligence; context modification
    • Implement data access for a tabular data model.
      • This objective may include but is not limited to: manage partitions; processing; Vertipaq versus Direct Query
  • Manage, Maintain, and Troubleshoot an SSAS Database (18%)
    • Analyze data model performance.
      • This objective may include but is not limited to: performance consequences of DWH design; optimize performance by changing the design of the cube or dimension; Analyze and optimize performances of an MDX/DAX query; optimize queries for huge data sets; optimize MDX in the calculations; performance monitor counters; DMVs; performance counters (new for tabular model), growth of the cache, logging options
    • Process data models.
      • This objective may include but is not limited to: processing tables or partitions for tabular models; processing databases, cubes, dimensions for multidimensional models; full processing versus incremental processing, remote processing; lazy aggregations; automate with Analysis Management Objects (AMO) or XML for Analysis (XMLA)
    • Troubleshoot data analysis issues.
      • This objective may include but is not limited to: use SQL Profiler; troubleshoot duplicate key dimension processing errors; error logs and event viewer logs of SSAS, mismatch of data: incorrect relationships or aggregations; dynamic security issues; validate logic and calculations
    • Deploy SSAS databases.
      • This objective may include but is not limited to: Deployment Wizard; BIDS; SSMS; automation; test solution post deployment; deciding whether or not to process
    • Install and maintain a SSAS instance.
      • This objective may include but is not limited to: software installation of SSAS; development tools, development and production box installation considerations; upgrade; data file and program file location, planning for Administrator accounts; Updates (service packs); install and maintain each instance type of Analysis Services, including PowerPivot; restore and import PowerPivot.
  • Build an Analysis Services Database (38%)
    • Design dimensions and measures.
      • This objective may include but is not limited to: given a requirement, identify the dimension/measure group relationship that should be selected; design patterns for representing business facts and dimensions (many-to-many relationships); design dimensions to support multiple related measure groups (many related fact tables); handle degenerate dimensions in a cube; identify the attributes for dimensions; identify the measures; aggregation behavior for the measures; hierarchies
    • Implement and configure dimensions in a cube.
      • This objective may include but is not limited to: translations; attribute relations; hierarchies; implement SQL Server Analysis Services (SSAS) dimensions and cubes; identify the Attribute Relationships that should be made for a given set of Attributes in a dimension; develop new custom attributes on dimensions; detect possible design flaws in attribute relationships; create attribute relationships correctly in an analysis services dimension; implement time Dimensions in cubes; manage SSAS parent-child dimensions; dimension type
    • Design a schema to support cube architecture.
      • 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; identify the appropriate data types with correct precision and size
    • Create measures.
      • This objective may include but is not limited to: logically group measures; select appropriate aggregation functions; format measures
    • Implement a cube.
      • This objective may include but is not limited to: use Business Intelligence Development Studio (BIDS) to build the cube; use BIDS to do non additive or semi additive measures in a cube; measures, perspectives; translations; dimension usage; cube specific dimension properties; measure groups; implement reference dimensions; implement many to many relationships; implement fact relationships; implement role-playing relationships; define granularity; create and manage linked measure groups and linked dimensions; actions
    • Create Multidimensional Expressions (MDX) queries.
      • This objective may include but is not limited to: 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; implement a custom MDX or logical solution for a pre-prepared case task; graphical query designer or the generic query designer
    • Implement custom logic in a data model.
      • Must include: Data Analysis Expressions (DAX) calculated columns and measures. This objective may include but is not limited to: key performance indicators (KPI); calculated members; use MDX functions to calculate members; relative Measures (growth, YoY, same period last year), % of total using MDX; named sets; adding intelligence to dimensions; Analysis Services stored procedures
    • Implement storage design in a multidimensional model.
      • This objective may include but is not limited to: aggregations; partitions; storage modes; proactive caching; manage write-back partitions
    • Select an appropriate model for data analysis.
      • This objective may include but is not limited to: UDM; Scalability, Cleansed; traditional hierarchical; high volume of data; advanced features (support for financial applications; many to many); organizational BI; Tabular Data Model: raw data; relational tables and relationships; simpler data structures; Team and personal BI; choose between multidimensional and tabular models
  • Build a Report with SQL Server Reporting Services (SSRS) (28%)
    • Design a report.
      • This objective may include but is not limited to: selecting report components (crosstab report, Tablix, design chart, data visualization components), report templates (Report Definition Language), identify the data source and parameters; designing a grouping structure; drill-down reports, drill-through reports; determine if any expressions are required to display data that is not coming directly from the data source
    • Implement a report layout.
      • This objective may include but is not limited to: formatting; apply conditional formatting; page configuration; headers and footers; matrix; table; chart; image; list; indicators, maps, grouping; use Report Builder to implement a report layout; creating a range of reports using different data regions; custom fields (implementing different parts of the report); collections (global collections); using expressions; data visualization components; identifying report parts; group variables and report variables
    • Configure authentication and authorization for a reporting solution.
      • This objective may include but is not limited to: configure server-level and item-level role-based security; configure Windows authentication and custom authentication (forms-based authentication); configure Reporting service security (setup or addition of role) ; authenticating against data source; storing credential information; describe Report Server security architecture and site level security; create system level roles; item level security; create a new role assignment; assign Windows users to roles; secure reports using roles; configure SharePoint groups and permissions
    • Implement interactivity in a report.
      • This objective may include but is not limited to: drilldown; drillthrough; interactive sorting; parameters: (databound parameters; multi-value parameters); create dynamic reports in SSRS using parameters; show/hide property; actions (jump to report); filters; parameter list; fixed headers; document map, embedded HTML
    • Troubleshoot reporting services issues.
      • This objective may include but is not limited to: querying the executionlog views in ReportServer database; viewing reportingservices log files; Windows Reliability and Performance monitor ; Using the ReportServer: Service and Web Service objects; long running reports; rendering; connectivity issues, use SQL Profiler; data reconciliation: incorrect relationships or aggregations; dynamic security issues; validate logic and calculations
    • Manage a report environment.
      • This objective may include but is not limited to: manage subscriptions and subscription settings, manage data sources, integrating SharePoint Server 2010; email delivery settings; managing the number of snapshots; manage schedules, manage running jobs, manage report server logs; manage report server databases, manage the encryption keys, setting up the execution log reporting; reviewing the reports; site level settings; design report lifecycle; automate management of reporting services; create a report organization structure; install and configure reporting services
    • Configure report data sources and datasets.
      • This objective may include but is not limited to: query types (stored procedure versus table versus text only); parameterized connection strings (dynamic connection strings); filter location (dataset vs. query); ; configure data source options i.e. extract and connect to different LOB platforms; shared and embedded data sources and datasets; connect to SQL Azure database; SQL Data Market; MDX queries; work with non-relational data sources such as xml or SharePoint

 

B. Designing business Intelligence Solutions with MS SQL 2012 467

  • 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 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.
      • 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 frontend; implement Dynamic Dimension Security within a cube; configure security for an Extranet environment; configure Kerberos Security; skills on 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.
      • This objective may include but is not limited to: 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.
      • This objective may include but is not limited to: design a High Availability (HA) and disaster recovery (DR) strategy; proactively preventing issues
    • Design a logging and auditing strategy.
      • This objective may include but is not limited to: design a new SSIS logging infrastructure (i.e. info available thru the catalog views); validate 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 versus filter-based processing; managing data sets through the use of stored procedures
    • Manage 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 info 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 needs 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.
      • 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/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.
      • This objective may include but is not limited to: design a data model that is optimized for reporting; design & 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.
      • 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 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.
      • 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 (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.
      • This objective may include but is not limited to: 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.
      • This objective may include but is not limited to: using new project deployment model; passing 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; 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.
      • This objective may include but is not limited to: avoid repeating Configuration Information entered in SSIS packages and use configuration files