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Baza wiedzy MSDN
MS-20767
Implementing a SQL Data Warehouse
szkolenie autoryzowane
cena / 1 osoba
3 850,00 zł
czas trwania
5 dni
dostępność onLine
zapytaj »
O szkoleniu
Dla kogo
The primary audience for this course are database professionals who need to fulfil a Business Intelligence Developer role. They will need to focus on hands-on work creating BI solutions including Data Warehouse implementation, ETL, and data cleansing.
Wymagania wstępne
In addition to their professional experience, students who attend this training should already have the following technical knowledge:
  • At least 2 years’ experience of working with relational databases, including:
  • Designing a normalized database.
  • Creating tables and relationships.
  • Querying with Transact-SQL.
  • Some exposure to basic programming constructs (such as looping and branching).
  • An awareness of key business priorities such as revenue, profitability, and financial accounting is desirable.
Zakres tematyczny
  • Introduction to Data Warehousing
    • Overview of Data Warehousing
    • Considerations for a Data Warehouse Solution
  • Planning Data Warehouse Infrastructure
    • Considerations for Building a Data Warehouse
    • Data Warehouse Reference Architectures and Appliances
  • Designing and Implementing a Data Warehouse
    • Logical Design for a Data Warehouse
    • Physical Design for a Data Warehouse
  • Columnstore Indexes
    • Introduction to Columnstore Indexes
    • Creating Columnstore Indexes
    • Working with Columnstore Indexes
  • Implementing an Azure SQL Data Warehouse
    • 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
  • Creating an ETL Solution
    • Introduction to ETL with SSIS
    • Exploring Source Data
    • Implementing Data Flow
  • Implementing Control Flow in an SSIS Package
    • Introduction to Control Flow
    • Creating Dynamic Packages
    • Using Containers
  • Debugging and Troubleshooting SSIS Packages
    • Debugging an SSIS Package
    • Logging SSIS Package Events
    • Handling Errors in an SSIS Package
  • Implementing an Incremental ETL Process
    • Introduction to Incremental ETL
    • Extracting Modified Data
    • Temporal Tables
  • Enforcing Data Quality
    • Introduction to Data Quality
    • Using Data Quality Services to Cleanse Data
    • Using Data Quality Services to Match Data
  • Using Master Data Services
    • Master Data Services Concepts
    • Implementing a Master Data Services Model
    • Managing Master Data
    • Creating a Master Data Hub
  • Extending SQL Server Integration Services (SSIS)
    • Using Custom Components in SSIS
    • Using Scripting in SSIS
  • Deploying and Configuring SSIS Packages
    • Overview of SSIS Deployment
    • Deploying SSIS Projects
    • Planning SSIS Package Execution
  • Consuming Data in a Data Warehouse
    • Introduction to Business Intelligence
    • Introduction to Reporting
    • An Introduction to Data Analysis
    • Analyzing Data with Azure SQL Data Warehouse
Zakres tematyczny szkolenia
Dla kogo
The primary audience for this course are database professionals who need to fulfil a Business Intelligence Developer role. They will need to focus on hands-on work creating BI solutions including Data Warehouse implementation, ETL, and data cleansing.
Wymagania wstępne
In addition to their professional experience, students who attend this training should already have the following technical knowledge:
  • At least 2 years’ experience of working with relational databases, including:
  • Designing a normalized database.
  • Creating tables and relationships.
  • Querying with Transact-SQL.
  • Some exposure to basic programming constructs (such as looping and branching).
  • An awareness of key business priorities such as revenue, profitability, and financial accounting is desirable.
Zakres tematyczny
  • Introduction to Data Warehousing
    • Overview of Data Warehousing
    • Considerations for a Data Warehouse Solution
  • Planning Data Warehouse Infrastructure
    • Considerations for Building a Data Warehouse
    • Data Warehouse Reference Architectures and Appliances
  • Designing and Implementing a Data Warehouse
    • Logical Design for a Data Warehouse
    • Physical Design for a Data Warehouse
  • Columnstore Indexes
    • Introduction to Columnstore Indexes
    • Creating Columnstore Indexes
    • Working with Columnstore Indexes
  • Implementing an Azure SQL Data Warehouse
    • 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
  • Creating an ETL Solution
    • Introduction to ETL with SSIS
    • Exploring Source Data
    • Implementing Data Flow
  • Implementing Control Flow in an SSIS Package
    • Introduction to Control Flow
    • Creating Dynamic Packages
    • Using Containers
  • Debugging and Troubleshooting SSIS Packages
    • Debugging an SSIS Package
    • Logging SSIS Package Events
    • Handling Errors in an SSIS Package
  • Implementing an Incremental ETL Process
    • Introduction to Incremental ETL
    • Extracting Modified Data
    • Temporal Tables
  • Enforcing Data Quality
    • Introduction to Data Quality
    • Using Data Quality Services to Cleanse Data
    • Using Data Quality Services to Match Data
  • Using Master Data Services
    • Master Data Services Concepts
    • Implementing a Master Data Services Model
    • Managing Master Data
    • Creating a Master Data Hub
  • Extending SQL Server Integration Services (SSIS)
    • Using Custom Components in SSIS
    • Using Scripting in SSIS
  • Deploying and Configuring SSIS Packages
    • Overview of SSIS Deployment
    • Deploying SSIS Projects
    • Planning SSIS Package Execution
  • Consuming Data in a Data Warehouse
    • Introduction to Business Intelligence
    • Introduction to Reporting
    • An Introduction to Data Analysis
    • Analyzing Data with Azure SQL Data Warehouse
O ośrodku szkoleniowym
Integral Technologies
ul. Wspólna 50A lok. 37, 00-684 Warszawa
MS-20767
Implementing a SQL Data Warehouse
czas trwania: 5 dni
Dla kogo
The primary audience for this course are database professionals who need to fulfil a Business Intelligence Developer role. They will need to focus on hands-on work creating BI solutions including Data Warehouse implementation, ETL, and data cleansing.
Wymagania wstępne
In addition to their professional experience, students who attend this training should already have the following technical knowledge:
  • At least 2 years’ experience of working with relational databases, including:
  • Designing a normalized database.
  • Creating tables and relationships.
  • Querying with Transact-SQL.
  • Some exposure to basic programming constructs (such as looping and branching).
  • An awareness of key business priorities such as revenue, profitability, and financial accounting is desirable.
Zakres tematyczny
  • Introduction to Data Warehousing
    • Overview of Data Warehousing
    • Considerations for a Data Warehouse Solution
  • Planning Data Warehouse Infrastructure
    • Considerations for Building a Data Warehouse
    • Data Warehouse Reference Architectures and Appliances
  • Designing and Implementing a Data Warehouse
    • Logical Design for a Data Warehouse
    • Physical Design for a Data Warehouse
  • Columnstore Indexes
    • Introduction to Columnstore Indexes
    • Creating Columnstore Indexes
    • Working with Columnstore Indexes
  • Implementing an Azure SQL Data Warehouse
    • 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
  • Creating an ETL Solution
    • Introduction to ETL with SSIS
    • Exploring Source Data
    • Implementing Data Flow
  • Implementing Control Flow in an SSIS Package
    • Introduction to Control Flow
    • Creating Dynamic Packages
    • Using Containers
  • Debugging and Troubleshooting SSIS Packages
    • Debugging an SSIS Package
    • Logging SSIS Package Events
    • Handling Errors in an SSIS Package
  • Implementing an Incremental ETL Process
    • Introduction to Incremental ETL
    • Extracting Modified Data
    • Temporal Tables
  • Enforcing Data Quality
    • Introduction to Data Quality
    • Using Data Quality Services to Cleanse Data
    • Using Data Quality Services to Match Data
  • Using Master Data Services
    • Master Data Services Concepts
    • Implementing a Master Data Services Model
    • Managing Master Data
    • Creating a Master Data Hub
  • Extending SQL Server Integration Services (SSIS)
    • Using Custom Components in SSIS
    • Using Scripting in SSIS
  • Deploying and Configuring SSIS Packages
    • Overview of SSIS Deployment
    • Deploying SSIS Projects
    • Planning SSIS Package Execution
  • Consuming Data in a Data Warehouse
    • Introduction to Business Intelligence
    • Introduction to Reporting
    • An Introduction to Data Analysis
    • Analyzing Data with Azure SQL Data Warehouse
 
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