Курс M20767: Реализация хранилищ данных SQL
Цена для физических лиц, р.: 29900Цена для юридических лиц, р.: 30900Цена вебинара для физических лиц, р.: 28900Цена вебинара для юридических лиц, р.: 28900
Продолжительность курса (дней): 5
Даты (день):
17.09.2018,
22.10.2018,
26.11.2018
Даты (вечер):
17.09.2018,
22.10.2018,
26.11.2018
Курс готовит к тестам:
Цель:
Необходимая подготовка:
Предварительный тест:
Результат:
План курса:
Module 1: Introduction to Data Warehousing
Describe data warehouse concepts and architecture considerations.
Overview of Data Warehousing
Considerations for a Data Warehouse Solution
Lab : Exploring a Data Warehouse Solution
Module 2: Planning Data Warehouse Infrastructure
This module describes the main hardware considerations for building a data warehouse.
Considerations for Building a Data Warehouse
Data Warehouse Reference Architectures and Appliances
Lab : Planning Data Warehouse Infrastructure
Module 3: Designing and Implementing a Data Warehouse
This module describes how you go about designing and implementing a schema for a data warehouse.
Logical Design for a Data Warehouse
Physical Design for a Data Warehouse
Lab : Implementing a Data Warehouse Schema
Module 4: Columnstore Indexes
This module introduces Columnstore Indexes.
Introduction to Columnstore Indexes
Creating Columnstore Indexes
Working with Columnstore Indexes
Lab : Using Columnstore Indexes
Module 5: Implementing an Azure SQL Data Warehouse
This module describes Azure SQL Data Warehouses and how to implement them.
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
Lab : Implementing an Azure SQL Data Warehouse
Module 6: Creating an ETL Solution
At the end of this module you will be able to implement data flow in a SSIS package.
Introduction to ETL with SSIS
Exploring Source Data
Implementing Data Flow
Lab : Implementing Data Flow in an SSIS Package
Module 7: Implementing Control Flow in an SSIS Package
This module describes implementing control flow in an SSIS package.
Introduction to Control Flow
Creating Dynamic Packages
Using Containers
Lab : Implementing Control Flow in an SSIS Package
Lab : Using Transactions and Checkpoints
Module 8: Debugging and Troubleshooting SSIS Packages
This module describes how to debug and troubleshoot SSIS packages.
Debugging an SSIS Package
Logging SSIS Package Events
Handling Errors in an SSIS Package
Lab : Debugging and Troubleshooting an SSIS Package
Module 9: Implementing an Incremental ETL Process
This module describes how to implement an SSIS solution that supports incremental DW loads and changing data.
Introduction to Incremental ETL
Extracting Modified Data
Temporal Tables
Lab : Extracting Modified Data
Lab : Loading Incremental Changes
Module 10: Enforcing Data Quality
This module describes how to implement data cleansing by using Microsoft Data Quality services.
Introduction to Data Quality
Using Data Quality Services to Cleanse Data
Using Data Quality Services to Match Data
Lab : Cleansing Data
Lab : De-duplicating Data
Module 11: Using Master Data Services
This module describes how to implement master data services to enforce data integrity at source.
Master Data Services Concepts
Implementing a Master Data Services Model
Managing Master Data
Creating a Master Data Hub
Lab : Implementing Master Data Services
Module 12: Extending SQL Server Integration Services (SSIS)
This module describes how to extend SSIS with custom scripts and components.
Using Custom Components in SSIS
Using Scripting in SSIS
Lab : Using Scripts and Custom Components
Module 13: Deploying and Configuring SSIS Packages
This module describes how to deploy and configure SSIS packages.
Overview of SSIS Deployment
Deploying SSIS Projects
Planning SSIS Package Execution
Lab : Deploying and Configuring SSIS Packages
Module 14: Consuming Data in a Data Warehouse
This module describes how to debug and troubleshoot SSIS packages.
Introduction to Business Intelligence
Introduction to Reporting
An Introduction to Data Analysis
Analyzing Data with Azure SQL Data Warehouse
Lab : Using Business Intelligence Tools
Спец. предложения
