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    Course 20767C: Implementing a SQL Data Warehouse Training

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

    • ✔ Course Duration : 40 hrs
    • ✔ Training Options : Live Online / Self-Paced / Classroom
    • ✔ Certification Pass : Guaranteed

    400+

    Professionals Trained

    20+

    Countries And Counting

    25+

    Corporates Served

    20+ hrs

    Workshop

    OVERVIEW LEARNING OBJECTIVES PRE-REQUISITES CURRICULUM FAQ CERTIFICATE

    Overview

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

    What you will Learn

    • 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

    PREREQUISITES

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

    CURRICULUM

    Learning Objectives:

  • 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
  • Learning Objectives:

  • 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
  • Learning Objectives:

  • This module describes how you go about designing and implementing a schema for a data warehouse.
  • Lessons:
  • Data warehouse design overview
  • 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
  • Learning Objectives:

  • 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
  • Learning Objectives:

  • 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
  • Learning Objectives:

  • 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
  • Learning Objectives:

  • 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
  • Learning Objectives:

  • 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
  • Learning Objectives:

  • 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
  • Learning Objectives:

  • 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
  • Learning Objectives:

  • 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
  • Learning Objectives:

  • 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
  • Learning Objectives:

  • 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
  • Learning Objectives:

  • 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
  • FAQs

    You can enroll for this classroom training online. Payments can be made using any of the following options and receipt of the same will be issued to the candidate automatically via email.
    1. Online ,By deposit the mildain bank account
    2. Pay by cash team training center location

    Highly qualified and certified instructors with 20+ years of experience deliver more than 200+ classroom training.

    Contact us using the form on the right of any page on the mildaintrainings website, or select the Live Chat link. Our customer service representatives will be able to give you more details.

    You will never miss a lecture at Mildaintrainigs! You can choose either of the two options: View the recorded session of the class available in your LMS. You can attend the missed session, in any other live batch.

    We have a limited number of participants in a live session to maintain the Quality Standards. So, unfortunately, participation in a live class without enrollment is not possible. However, you can go through the sample class recording and it would give you a clear insight about how are the classes conducted, quality of instructors and the level of interaction in a class.

    Yes, the access to the course material will be available for lifetime once you have enrolled into the course.

    Just give us a CALL at +91 8447121833 OR email at [email protected]

    CERTIFICATE OF ACHIEVEMENT

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    Online Live Instructor-Led Classes.
    Classroom Classes at our/your premises.
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  • Real-life Case Studies
    Live project based on any of the selected use cases, involving implementation of the various Course concepts.
  • Assignments
    Each class will be followed by practical assignments.
  • Lifetime Access
    You get lifetime access to presentations, quizzes, installation guide & class recordings.
  • 24 x 7 Expert Support
    We have 24x7 online support team to resolve all your technical queries, through ticket based tracking system, for the lifetime.
  • Certification
    Sucessfully complete your final course project and Mildaintrainings will give you Course completion certificate.
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