dataWarehousing with mS SQL server

By attending DataWarehousing with MS SQL Server workshop, Delegates will learn -

  • Data warehouse concepts and architecture considerations
  • Select an appropriate hardware platform for a data warehouse
  • Design and implement a data warehouse
  • Implement data flow and control flow in a SSIS package
  • Debug and troubleshoot SSIS packages
  • Implement a SSIS solution that supports incremental data warehouse loads and extracting data
  • Implement data cleansing using Microsoft DQS
  • Implement Master Data Services (MDS) to enforce data integrity
  • Extend SSIS with custom scripts and components
  • Deploy and configure SSIS packages
  • How Business Intelligence solutions consume data in a data warehouse

In DataWarehousing with MS SQL Server training course, Delegates will learn how to implement a data warehouse platform to support a business intelligence (BI) solution. They will discover how to create a data warehouse, implement extract, transform, and load (ETL) with SQL Server Integration Services (SSIS), and validate and cleanse data with SQL Server Data Quality Services (DQS) and SQL Server Master Data Services.

  • Minimum two years experience working with relational databases, including designing a normalized database, creating tables and relationships
  • Basic programming constructs, including looping and branching
  • Focus on key business priorities, such as revenue, profitability, and financial account

  • Database professionals who need to fulfill a BI developer role focused on hands-on work, creating BI solutions included data warehouse implementation, ETL, and data cleansing
  • Database professionals responsible for implementing a data warehouse, developing SSIS packages for data extraction, loading, transferring, transforming, and enforcing data integrity using MDS, and cleansing data using DQS

COURSE AGENDA

  • ETL with SSIS
  • Explore Source Data
  • Implement Data Flow
  • Logical Design, Including Dimension Tables and Fact Tables
  • Physical Implementation, Including a Star Schema, Snowflake Schema, and Time Dimension
  • Hardware Selections
  • Considerations for Business Intelligence Infrastructure
  • Concepts and Architecture Considerations
  • Considerations for a Data Warehouse Solution
  • Control Flow
  • Create Dynamic Packages
  • Using Containers
  • Manage Consistency with Transactions and Checkpoints
  • Debug an SSIS Package
  • Log SSIS Package Events
  • Implement an Event Handler
  • Handle Errors in an SSIS Package
  • Incremental ETL
  • Data and Modified Data Extraction
  • Data and Modified Data Load planning
  • Incremental loads Using SSIS
  • Transact-SQL Loading Techniques
  • Microsoft SQL Server DQS
  • Use DQS to Cleanse Data
  • Use DQS to Match Data
  • Master Data Services Concepts
  • Implement a Master Data Services Model
  • Master Data Services Tools to Manage and Create Master Data
  • Custom Components in SSIS
  • Scripting in SSIS
  • Deployment Considerations
  • Deploy SSIS Projects
  • Plan SSIS Package Execution
  • Business Intelligence Solutions
  • Enterprise BI Solution
  • Self-Service BI and Big Data Solutions