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Analytics and Data Management Courses Course Details
Cursusbeschrijving
This course is part 1 of the Microsoft MCSA: SQL Server 2016 – Business Intelligence Development training and certification programme. Get your Microsoft Implementing a SQL Data Warehouse training in just 3 days and learn more than you could imagine. You’ll use Official Course materials. You’ll also use Insoft’s unique Lecture | Lab | Review technique, which will immerse you in topics like:
- Designing and implementing a data warehouse
- Implementing an Azure SQL data warehouse
At Insoft we know your time is valuable. That’s why we give you the opportunity to gain your Microsoft Implementing a SQL Data Warehouse Training in just 3 days. We provide the best conditions for you to learn. With us by your side, encouraging and guiding you along the way, you can enjoy 3 intense, focused days of quality learning in a distraction free environment. Your expert instructor will be working with Insoft’s unique accelerated learning methods, which include our exclusive lecture/lab/review methodology with real life cases putting you in the best possible position to learn and retain knowledge. Sitting your Microsoft Implementing a SQL Data Warehouse Course with Insoft, means:
- You’ll get more hours of training per day, allowing you to get trained faster and more cost-effectively than with any other training provider.
- You will be trained by one of the most expert instructors in the world.
- You can focus purely on learning in our distraction free environment.
- Dedicated onsite support and access to your classroom at all hours.
- The price you pay is all-inclusive and covers all course materials, exams, transportation service, accommodation and meals.
- The Certification Guarantee allows you to train again for free, if you do not pass first time. You only pay for any exams and labs, and accommodation.
This training already retired on 30th of June 2020.
Inhoud
Module 1: Introduction to Data Warehousing
Describe data warehouse concepts and architecture considerations.
Lessons
Overview of Data Warehousing
Considerations for a Data Warehouse Solution
Lab : Exploring a Data Warehouse Solution
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 Building a Data Warehouse
Data Warehouse Reference Architectures and Appliances
Lab : Planning Data Warehouse Infrastructure
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
Logical Design for a Data Warehouse
Physical Design for a Data Warehouse
Lab : Implementing a Data Warehouse Schema
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
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
Lab : Implementing an Azure SQL Data Warehouse
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
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
Lab : Implementing Control Flow in an SSIS Package
Lab : Using Transactions and 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
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 an Incremental ETL Process
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
Temporal Tables
Lab : Extracting Modified Data
Lab : Loading Incremental Changes
After completing this module, you will be able to:
Describe incremental ETL
Extract 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
Lab : De-duplicating 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
Master Data Services Concepts
Implementing a Master Data Services Model
Managing Master Data
Creating a Master Data Hub
Lab : Implementing Master Data Services
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 Custom Components in SSIS
Using Scripting in SSIS
Lab : Using Scripts and Custom Components
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
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
Introduction to Reporting
An Introduction to Data Analysis
Analysing Data with Azure SQL Data Warehouse
Lab : Using Business Intelligence Tools
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
Analyse data with Azure SQL data warehouse
Voorkennis
It is recommended you have at least 2 years’ experience of working with relational databases, including:
- Designing a normalised database
- Creating tables and relationships
- 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 Do you have what it takes? We´ll help you decide – Call us to discuss your technical background, experience and qualifications to determine how we can help you succeed in this course. Just call us and speak to one of our enrolment consultants.