Designing Business Intelligence Solutions with Microsoft SQL Server Chris Testa-O’Neill | Principal Consultant | Claribi Charley Hanania | Principal Consultant | QS2 AG – Quality Software Solutions

Meet Chris Testa-O’Neill | ‏@ctesta_oneill

Meet Charley Hanania | ‏@charleyhanania MCT Regional Lead - Switzerland Regional Mentor - Western Europe Chapter Leader - Switzerland Joint Country Lead - Switzerland

Course Topics Implementing Data Models and Reports with Microsoft SQL Server 01 | Planning a SQL Server BI Solution 04 | Design an ETL Solution 02 | Designing a BI Infrastructure 05 | Design BI Data Models 03 | Design a Data Warehouse 06 | Designing Reporting Services Solutions

Setting Expectations Target Audience Business Intelligence Architects, Developers Suggested Prerequisites/Supporting Material A basic understanding of dimensional modeling (star schema) for data warehouses The ability to create Integration Services packages that include control flows and data flows The ability to create a basic multidimensional cube with Analysis Services The ability to create a basic tabular model with PowerPivot and Analysis Services The ability to create Reporting Services reports with Report Designer

01 | Planning a SQL Server BI Solution Chris Testa-O’Neill | Principal Consultant | Claribi Charley Hanania | Principal Consultant | QS2 AG – Quality Software Solutions

Module Overview Gathering Requirements. Components of a BI Infrastructure Plan a Data Warehouse. Plan ETL Infrastructure. Plan Data Models. Plan Reporting Services Infrastructure.

Gathering Requirements

Gathering Requirements Business: Goals Objectives Budgets Timescales Operations time Compliance Legal Technical: Functional Performance Availability Scalability Disaster Recovery

Components of a BI Infrastructure

Components of a BI Infrastructure Data Warehouse Master Data Management Data Cleansing Data Sources  ETL Data Models Reporting and Analysis

Plan for a Data Warehouse

Plan for a Data Warehouse Reporting and Analysis Kimball Dimensional Data Marts Inmon Corporate Information Factory Central Dimensional Data Warehouse Federated Hub and Spoke Data Cleansing Data Models Data Sources Data Warehouse  ETL Master Data Management

Plan an ETL Infrastructure

Plan an ETL Infrastructure Reporting and Analysis Enterprise Integration Management ETL: Extract from sources Transform schema & content Load into destination Data Cleansing: Data value validation Duplicate record matching Master Data Management: Business entity integrity Data Cleansing Data Models Data Sources Data Warehouse  ETL Master Data Management

Plan Data Models

Plan Data Models  Data Sources Data Warehouse ETL Reporting and Analysis Benefits of data models: Abstract data warehouse tables Simplify analysis for users Add business logic Pre-aggregate measures Provide a standard interface Types of models: Multidimensional Tabular Data Cleansing Data Models Data Sources Data Warehouse  ETL Master Data Management

Plan Reporting Services Infrastructure

Plan Reporting Services infrastructure IT-provided reports Self-service reporting Interactive analysis Dashboards and scorecards Data mining Reporting and Analysis Data Cleansing Data Models Data Sources Data Warehouse  ETL Master Data Management