Developing SQL Databases (Course OD20762A - Exam 70-762) - nanforiberica

Acerca de este curso

This 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.

Perfil del usuario objetivo

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. 

Al finalizar el curso

After completing this course, students will be able to:

  • Provision a Database Server.
  • Upgrade SQL Server.
  • Configure SQL Server.
  • Manage Databases and Files (shared).

      Requisitos previos

      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.

      Detalles del Curso

      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

         

            Para más información sobre cómo realizar un MOC On-Demand, preguntas frecuentes, y términos y condiciones pulse aquí.

            €655.00