Implementing a Data Warehouse with Microsoft SQL Server 2014 (90 Day)

Course Details
Code: OD20463
Tuition (USD): $870.00 $652.50 • Self Paced
This course is available in other formats
Instructor-Led Classroom & Virtual
Implementing a Data Warehouse with Microsoft SQL Server 2014 (20463)

Data warehousing is a solution organizations use to centralize business data for reporting and analysis. This course focuses on teaching individuals how to create a data warehouse with SQL Server 2014, and implement ETL with SQL Server Integration Services. This course helps people prepare for exam 70-463.
Thiscourse describes how to implement a data warehouse platform to support a BIsolution. Students will learn how to create a data warehouse with MicrosoftSQL Server 2014, implement ETL with SQL Server Integration Services, andvalidate and cleanse data with SQL Server Data Quality Services and SQL ServerMaster Data Services.Note:This course is designed for customers who are interested in learning SQL Server2012 or SQL Server 2014. It covers the new features in SQL Server 2014, butalso the important capabilities across the SQL Server data platform.

Skills Gained

  • 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

Who Can Benefit

This course is intended for databaseprofessionals who need to fulfil a Business Intelligence Developer role.  They will need to focus on hands-on workcreating BI solutions including Data Warehouse implementation, ETL, and datacleansing. Primary responsibilities include:

  • Implementing a data warehouse.
  • Developing SSIS packages for data extraction, transformation, and loading.
  • Enforcing data integrity by using Master Data Services.
  • Cleansing data by using Data Quality Services.

Prerequisites

Thiscourse requires that you meet the following prerequisites:

  • At least 2 yearsexperience of working with relational databases, including:
  • Designing anormalized database.
  • Creating tablesand relationships.
  • Querying withTransact-SQL.
  • Some exposure tobasic programming constructs (such as looping and branching).
An awareness of key business priorities such as revenue,profitability, and financial accounting is desirable.

Course Details

Outline

Module 1: Introduction to Data WarehousingThis module provides an introduction to the key components of a data warehousing solution and the high-level considerations you must take into account when you embark on a data warehousing project.
Lessons

  • Overview of Data Warehousing
  • Considerations for a Data Warehouse Solution
Lab : Exploring a Data Warehousing SolutionAftercompleting this module, you will be able to:
  • Describe the key elements of a data warehousing solution
  • Describe the key considerations for a data warehousing project
Module 2: Data Warehouse Hardware ConsiderationsThis module discusses considerations for selecting hardware and distributing SQL Server facilities across servers.
Lessons
  • Considerations for building a Data Warehouse
  • Data Warehouse Reference Architectures and Appliances
Lab : Planning Data Warehouse InfrastructureAfter completing this module, you will be able to:
  • Describe key considerations for BIinfrastructure.
  • Plan data warehouse infrastructure.
Module 3: Designing and Implementing a Data WarehouseThis module describes the key considerations for the logical design of a data warehouse, and then discusses best practices for its physical implementation.
Lessons
  • Logical Design for a Data Warehouse
  • Physical design for a data warehouse
Lab : Implementing a Data Warehouse SchemaAftercompleting this module, you will be able to:
  • Describe a processfor designing a dimensional model for a data warehouse
  • Design dimensiontables for a data warehouse
  • Design fact tablesfor a data warehouse
  • Design and implement effective physical datastructures for a data warehouse





Module 4: Creating an ETL Solution with SSISThis module discusses considerations for implementing an ETL process, and then focuses on Microsoft SQL Server Integration Services (SSIS) as a platform for building ETL solutions.
Lessons
  • Introduction to ETL with SSIS
  • Exploring Data Sources
  • Implementing Data Flow
Lab : Implementing Data Flow in an SSIS PackageAfter completing thismodule, you will be able to:
  • Describe the keyfeatures of SSIS.
  • Explore sourcedata for an ETL solution.
  • Implement a data flow by using SSIS
Module 5: Implementing Control Flow in an SSIS PackageThis module describes how to implement ETL solutions that combine multiple tasks and workflow logic.
Lessons
  • Introduction to Control Flow
  • Creating Dynamic Packages
  • Using Containers
  • Managing Consistency
Lab : Implementing Control Flow in an SSIS PackageLab : Using Transactions and CheckpointsAftercompleting this module, you will be able to:
  • Implement controlflow with tasks and precedence constraints
  • Create dynamicpackages that include variables and parameters
  • Use containers ina package control flow
  • Enforce consistency with transactions andcheckpoints
Module 6: Debugging and Troubleshooting SSIS PackagesThis module describes how you can debug packages to find the cause of errors that occur during execution. It then discusses the logging functionality built into SSIS that you can use to log events for troubleshooting purposes. Finally, the module describes common approaches for handling errors in control flow and data flow.
Lessons
  • Debugging an SSIS Package
  • Logging SSIS Package Events
  • Handling Errors in an SSIS Package
Lab : Debugging and Troubleshooting an SSIS PackageAfter completing this module, you will beable to:
  • Debug an SSISpackage
  • Implement loggingfor an SSIS package
  • Handle errors in an SSIS package
Module 7: Implementing an Incremental ETL ProcessThis module describes the techniques you can use to implement an incremental data warehouse refresh process.
Lessons
  • Introduction to Incremental ETL
  • Extracting Modified Data
  • Loading Modified data
Lab : Extracting Modified DataLab : Loading Incremental ChangesAfter completing this module, you will beable to:
  • Plan dataextraction
  • Extract modified data
Module 8: Enforcing Data QualityThis module introduces Microsoft SQL Server Data Quality Services (DQS), and describes how you can use it to cleanse and deduplicate data.
Lessons
  • Introduction to Data Quality
  • Using Data Quality Services to Cleanse Data
  • Using Data Quality Services to Match data
Lab : Cleansing DataLab : De-duplicating dataAfter completing thismodule, you will be able to:
  • Describe how DataQuality Services can help you manage data quality
  • Use Data QualityServices to cleanse your data
  • Use Data Quality Services to match data
Module 9: Enforcing Data QualityEnsuring the high quality of data is essential if the results of data analysis are to be trusted. SQL Server 2014 includes Data Quality Services (DQS) to provide a computer-assisted process for cleansing data values, as well as identifying and removing duplicate data entities. This process reduces the workload of the data steward to a minimum while maintaining human interaction to ensure accurate results.
Lessons
  • Introduction to Data Quality
  • Using Data Quality Services to Cleanse Data
  • Using Data Quality Services to Match Data
Lab : Cleansing DataLab : Deduplicating DataAfter completing this module, you will be able to:
Describe how DQS can help you manage data quality.
Use DQS to cleanse your data.
Use DQS to match data.