Arrow Electronics, Inc.

Implementing a SQL Data Warehouse

CODE: MCS_20767

DURÉE: 5 Jours

PRIX H.T.: €2 830,00

Description

This five-day instructor-led course provides students with the knowledge and skills to provision a Microsoft SQL Server 2016 database. The course covers SQL Server 2016 provision both on-premise and in Azure, and covers installing from new and migrating from an existing install.

Objectifs

After completing this course, students will be able to:

    Describe the key elements of a data warehousing solution
    Describe the main hardware considerations for building a data warehouse
    Implement a logical design for a data warehouse
    Implement a physical design for a data warehouse
    Create columnstore indexes
    Implementing an Azure SQL Data Warehouse
    Describe the key features of SSIS
    Implement a data flow by using SSIS
    Implement control flow by using tasks and precedence constraints
    Create dynamic packages that include variables and parameters
    Debug SSIS packages
    Describe the considerations for implement an ETL solution
    Implement Data Quality Services
    Implement a Master Data Services model
    Describe how you can use custom components to extend SSIS
    Deploy SSIS projects
    Describe BI and common BI scenarios

Audience

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.

Prérequis

In addition to their professional experience, students who attend this training should already have the following technical knowledge:

    Basic knowledge of the Microsoft Windows operating system and its core functionality.
    Working knowledge of relational databases.
    Some experience with database design.

Programme

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

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 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

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 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

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 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

After completing this module, you will be able to:

    Create Columnstore indexes

    Work with Columnstore Indexes

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

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 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

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 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

After completing this module, you will be able to:

    Describe control flow

    Create dynamic packages

    Use containers

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

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 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

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 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

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 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

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 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

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 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

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

Dates de session
Date
Lieu
Time Zone
Langue
Type
Garanti
PRIX H.T.

24 oct. 2021

English

MOC On Demand

€795,00

15 nov. 2021

Paris

CET

English

Classroom

€2 830,00