Microsoft Business Intelligence End to End with SQL Server 2008 R2 and SharePoint 2010

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Description

Prerequisites:

* Basic knowledge of Business Intelligence
* Knowledge of relational database systems
* Delegates will gain the most from this course if they are experienced with SQL Server database to the level of Microsoft course M2779 or M6232. However, as minimum requirement, delegates should have a good working knowledge of T-SQL to level of M50027 or M2778

Course Description:

Business intelligence solutions provide the infrastructure that enables users at all levels of a business to make better decisions based on more accurate and up-to-date information. This workshop focuses on teaching IT professionals the best practices and skills required to successfully design, build and operate a bus…

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Prerequisites:

* Basic knowledge of Business Intelligence
* Knowledge of relational database systems
* Delegates will gain the most from this course if they are experienced with SQL Server database to the level of Microsoft course M2779 or M6232. However, as minimum requirement, delegates should have a good working knowledge of T-SQL to level of M50027 or M2778

Course Description:

Business intelligence solutions provide the infrastructure that enables users at all levels of a business to make better decisions based on more accurate and up-to-date information. This workshop focuses on teaching IT professionals the best practices and skills required to successfully design, build and operate a business intelligence solution using SQL Server 2008 R2 Integration Services, Analysis Services, Reporting Services, PerformancePoint Monitoring/Analytics and ProClarity.

This course includes the following modules:

Business Intelligence Overview

  • Business intelligence (BI)
  • Extract Transform and Load (ETL)
  • SQL Server Integration Services (SSIS)
  • SQL Server Analysis Services (SSAS)
  • SQL Server Reporting Services (SSRS)
  • PerformancePoint Services for SharePoint
  • ProClarity
  • SharePoint
  • Master Data Management (MDM)
  • Evaluating BI requirements
  • Documenting requirements

Designing Business Intelligence Solution

  • Reviewing requirements
  • Identify each products role in the BI solution
  • Discuss whether to use a staging database
  • Discuss use of slowly changing dimensions (SCD)
  • Introduce temporal / rapidly changing dimensions (RCD)
  • Discuss use of surrogate keys
  • Discuss data warehousing techniques
  • Discuss timely delivery of data from source to destination (daily, hourly, real-time)
  • Discuss data warehouse schema design with advantages and disadvantages
  • Discuss designing a time dimension
  • Labs:
  • Documentation of requirements
  • Map source data onto output requirements
  • Flow of data from line of business to user interface

Creating the Data Warehouse

  • Table design (Partitioned tables, Primary and foreign keys, Data types, Logging and error tables)
  • Index considerations (Clustered, Non-clustered, Disabling and rebuilding indexes)
  • Labs:
  • Create data warehouse database
  • Create the dimension tables
  • Create the fact tables with partitioning
  • Create logging and error recording tables
  • Create indexes on the fact and dimension tables

Loading the Data Warehouse

  • SSIS basics (Packages, Control Flow, Data Flow, Transformations, Data Sources, Data Destinations)
  • Configurations
  • Logging
  • Lookups
  • Fast-load and table partitioning
  • Using switch and merge
  • Late arriving data
  • Change Data Capture (CDC SQL 2008 sources only)
  • Package design
  • Transactions
  • Checkpoints
  • Labs:
  • Design and create a SSIS package structure
  • Design the dimension load process using slowly changing dimension transformation (SCD)
  • Add control and data flow items
  • Use SSIS for lineage, logging, configurations and variables
  • Create data flow for each dimension table
  • Create data flow for each fact table

Creating the Analysis Cube

  • Data source views (Friendly names, Relationships, Calculated columns, Named queries)
  • Dimensions (Time, Parent-Child, Multiple table, Unary Operator)
  • Dimension Attributes (Key values and display values, Attribute relationships)
  • Measures (Data type design, Aggregations (Additive / Semi-Additive / Non-Additive))
  • Cubes (Producing the base cube, Dimensions usage and relationships)
  • Best practice warnings
  • Labs:
  • Designing dimensions for usability to required design
  • Design cube using dimensions
  • Set properties for measures

Enhancing the Analysis Cube

  • Cubes
  • Calculated measures andmembers
  • Names sets (Dynamic / Static)
  • Key Performance Indicators (KPI)
  • Perspectives, Actions, Partitions
  • Storage design
  • Designing aggregations
  • User-based optimisation (UBO)
  • Partition slice alignment
  • Security Roles
  • Processing design
  • Labs:
  • Create calculated measures (profit, profit%)
  • Create calculated members (total sales amount)
  • Create named sets (Europe : {[France],[UK],[Germany]})
  • Create KPI (profit% > 30%)
  • Create actions (Drillthrough)
  • Design partitions to correlate to the table partitioning and slices
  • Design perspectives for Internet and Reseller sales departments
  • Implement security roles for Internet and Reseller departments
  • Update SSIS control flow to include processing for SSAS dimensions and cubes

Producing the User Interface

  • Best Tool for the job
  • Infrastructure design
  • Where to use SSRS , PAS, PerformancePoint

Creating reports with Reporting Services

  • Show differences between BIDS and Report Builder 2.
  • Creating a report
  • Tools (Tablix, Gauges, Charts)
  • Related reports
  • Parameters
  • Deploying (Standalone SSRS, SharePoint Integrated)
  • Lab: Create a report to show sales for regions compared to last year

Creating dashboards with Excel PowerPivot

  • Describe positioning of Microsoft PowerPivot
  • Designing pages
  • Saving and publishing PowerPivot views
  • Introduce slicers
  • Lab: Excel Powerpivot working with multiple sources (SSAS, text file and Access)

Creating dashboards with PerformancePoint Services

  • Dashboard design best practice
  • Data Sources
  • Reports (Analytic Chart, Analytic Grid, SSRS Report, ProClarity Page, Scorecard, Strategy Map)
  • Dashboard
  • Labs:
  • Show dashboard design to best practice (ref. Stephen Few ?¢‚Äöá®?¨Information Dashboard Design)
  • Create a data source from SSAS cube created earlier
  • Create an analytic chart and grid, include parameters, for sales over time
  • Create a KPI for sales against last year
  • Create a scorecard using the KPI and include multiple target columns for target, score and indicator
  • Create a summary dashboard holding overview reports and scorecard
  • Introduce filters into the dashboards and relate published reports to filters
  • Publish dashboards to SharePoint

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