Curso 20767C: Implementing a SQL Data Warehouse

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• Conteúdo Programático:

  Module 1: Introduction to Data WarehousingThis module describes data warehouse concepts and architecture consideration.Lessons

  • Overview of Data Warehousing
  • Considerations for a Data Warehouse Solution

  Lab : Exploring a Data Warehouse Solution

  • Exploring data sources
  • Exploring an ETL process
  • Exploring a data warehouse

  After completing this module, you will be able to:

  • Describe the key elements of a data warehousing solution

  • Describe the key considerations for a data warehousing solution

  Module 2: Planning Data Warehouse InfrastructureThis module describes the main hardware considerations for building a data warehouse.Lessons

  • Considerations for data warehouse infrastructure.
  • Planning data warehouse hardware.

  Lab : Planning Data Warehouse Infrastructure

  • Planning data warehouse hardware

  After completing this module, you will be able to:

  • Describe the main hardware considerations for building a data warehouse

  • Explain how to use reference architectures and data warehouse appliances to create a data warehouse

  Module 3: Designing and Implementing a Data WarehouseThis module describes how you go about designing and implementing a schema for a data warehouse.Lessons

  • Data warehouse design overview
  • Designing dimension tables
  • Designing fact tables
  • Physical Design for a Data Warehouse

  Lab : Implementing a Data Warehouse Schema

  • Implementing a star schema
  • Implementing a snowflake schema
  • Implementing a time dimension table

  After completing this module, you will be able to:

  • Implement a logical design for a data warehouse

  • Implement a physical design for a data warehouse

  Module 4: Columnstore IndexesThis module introduces Columnstore Indexes.Lessons

  • Introduction to Columnstore Indexes
  • Creating Columnstore Indexes
  • Working with Columnstore Indexes

  Lab : Using Columnstore Indexes

  • Create a Columnstore index on the FactProductInventory table
  • Create a Columnstore index on the FactInternetSales table
  • Create a memory optimized Columnstore table

  After completing this module, you will be able to:

  • Create Columnstore indexes

  • Work with Columnstore Indexes

  Module 5: Implementing an Azure SQL Data WarehouseThis module describes Azure SQL Data Warehouses and how to implement them.Lessons

  • Advantages of Azure SQL Data Warehouse
  • Implementing an Azure SQL Data Warehouse
  • Developing an Azure SQL Data Warehouse
  • Migrating to an Azure SQ Data Warehouse
  • Copying data with the Azure data factory

  Lab : Implementing an Azure SQL Data Warehouse

  • Create an Azure SQL data warehouse database
  • Migrate to an Azure SQL Data warehouse database
  • Copy data with the Azure data factory

  After completing this module, you will be able to:

  • Describe the advantages of Azure SQL Data Warehouse

  • Implement an Azure SQL Data Warehouse

  • Describe the considerations for developing an Azure SQL Data Warehouse

  • Plan for migrating to Azure SQL Data Warehouse

  Module 6: Creating an ETL SolutionAt the end of this module you will be able to implement data flow in a SSIS package.Lessons

  • Introduction to ETL with SSIS
  • Exploring Source Data
  • Implementing Data Flow

  Lab : Implementing Data Flow in an SSIS Package

  • Exploring source data
  • Transferring data by using a data row task
  • Using transformation components in a data row

  After completing this module, you will be able to:

  • Describe ETL with SSIS

  • Explore Source Data

  • Implement a Data Flow

  Module 7: Implementing Control Flow in an SSIS PackageThis module describes implementing control flow in an SSIS package.Lessons

  • Introduction to Control Flow
  • Creating Dynamic Packages
  • Using Containers
  • Managing consistency.

  Lab : Implementing Control Flow in an SSIS Package

  • Using tasks and precedence in a control flow
  • Using variables and parameters
  • Using containers

  Lab : Using Transactions and Checkpoints

  • Using transactions
  • Using checkpoints

  After completing this module, you will be able to:

  • Describe control flow

  • Create dynamic packages

  • Use containers

  Module 8: Debugging and Troubleshooting SSIS PackagesThis module describes how to debug and troubleshoot SSIS packages.Lessons

  • Debugging an SSIS Package
  • Logging SSIS Package Events
  • Handling Errors in an SSIS Package

  Lab : Debugging and Troubleshooting an SSIS Package

  • Debugging an SSIS package
  • Logging SSIS package execution
  • Implementing an event handler
  • Handling errors in data flow

  After completing this module, you will be able to:

  • Debug an SSIS package

  • Log SSIS package events

  • Handle errors in an SSIS package

  Module 9: Implementing a Data Extraction SolutionThis module describes how to implement an SSIS solution that supports incremental DW loads and changing data.Lessons

  • Introduction to Incremental ETL
  • Extracting Modified Data
  • Loading modified data
  • Temporal Tables

  Lab : Extracting Modified Data

  • Using a datetime column to incrementally extract data
  • Using change data capture
  • Using the CDC control task
  • Using change tracking

  Lab : Loading a data warehouse

  • Loading data from CDC output tables
  • Using a lookup transformation to insert or update dimension data
  • Implementing a slowly changing dimension
  • Using the merge statement

  After completing this module, you will be able to:

  • Describe incremental ETL

  • Extract modified data

  • Load modified data.

  • Describe temporal tables

  Module 10: Enforcing Data QualityThis module describes how to implement data cleansing by using Microsoft Data Quality services.Lessons

  • Introduction to Data Quality
  • Using Data Quality Services to Cleanse Data
  • Using Data Quality Services to Match Data

  Lab : Cleansing Data

  • Creating a DQS knowledge base
  • Using a DQS project to cleanse data
  • Using DQS in an SSIS package

  Lab : De-duplicating Data

  • Creating a matching policy
  • Using a DS project to match data

  After completing this module, you will be able to:

  • Describe data quality services

  • Cleanse data using data quality services

  • Match data using data quality services

  • De-duplicate data using data quality services

  Module 11: Using Master Data ServicesThis module describes how to implement master data services to enforce data integrity at source.Lessons

  • Introduction to Master Data Services
  • Implementing a Master Data Services Model
  • Hierarchies and collections
  • Creating a Master Data Hub

  Lab : Implementing Master Data Services

  • Creating a master data services model
  • Using the master data services add-in for Excel
  • Enforcing business rules
  • Loading data into a model
  • Consuming master data services data

  After completing this module, you will be able to:

  • Describe the key concepts of master data services

  • Implement a master data service model

  • Manage master data

  • Create a master data hub

  Module 12: Extending SQL Server Integration Services (SSIS)This module describes how to extend SSIS with custom scripts and components.Lessons

  • Using scripting in SSIS
  • Using custom components in SSIS

  Lab : Using scripts

  • Using a script task

  After completing this module, you will be able to:

  • Use custom components in SSIS

  • Use scripting in SSIS

  Module 13: Deploying and Configuring SSIS PackagesThis module describes how to deploy and configure SSIS packages.Lessons

  • Overview of SSIS Deployment
  • Deploying SSIS Projects
  • Planning SSIS Package Execution

  Lab : Deploying and Configuring SSIS Packages

  • Creating an SSIS catalog
  • Deploying an SSIS project
  • Creating environments for an SSIS solution
  • Running an SSIS package in SQL server management studio
  • Scheduling SSIS packages with SQL server agent

  After completing this module, you will be able to:

  • Describe an SSIS deployment

  • Deploy an SSIS package

  • Plan SSIS package execution

  Module 14: Consuming Data in a Data WarehouseThis module describes how to debug and troubleshoot SSIS packages.Lessons

  • Introduction to Business Intelligence
  • An Introduction to Data Analysis
  • Introduction to reporting
  • Analyzing Data with Azure SQL Data Warehouse

  Lab : Using a data warehouse

  • Exploring a reporting services report
  • Exploring a PowerPivot workbook
  • Exploring a power view report

  After completing this module, you will be able to:

  • Describe at a high level business intelligence

  • Show an understanding of reporting

  • Show an understanding of data analysis

  • Analyze data with Azure SQL data warehouse

• Pré-Requisito:

  Além de sua experiência profissional, os alunos que frequentam esse treinamento já devem ter os seguintes conhecimentos técnicos:

  
  

  Conhecimento básico do sistema operacional Microsoft Windows e suas principais funcionalidades.

  Conhecimento prático de bancos de dados relacionais.

  Alguma experiência com design de banco de dados.

• Informações Adicionais:

  
  

• Material Didático: