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Implementing a SQL Data Warehouse with Microsoft SQL Server

Πρόσθετες Πληροφορίες

  • Συνοπτικό πρόγραμμα:

    Module 1: Introduction to Data Warehousing This 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

    Module 2: Planning Data Warehouse Infrastructure This 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


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


    Lessons:

    • 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
    • Module 4: Columnstore Indexes This 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


    Module 5: Implementing an Azure SQL Data Warehouse This 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

    Module 6: Creating an ETL Solution At 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

    Module 7: Implementing Control Flow in an SSIS Package This 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

    Module 8: Debugging and Troubleshooting SSIS Packages This 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

    Module 9: Implementing a Data Extraction Solution This 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

    Module 10: Enforcing Data Quality This 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

    Module 11: Using Master Data Services This 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

    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

    Module 13: Deploying and Configuring SSIS Packages This 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

    Module 14: Consuming Data in a Data Warehouse This 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
  • Διάρκεια: 40 Ώρες
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