This Data Warehouse With Microsoft SQL Server 2014 training teach you how to implement a data warehouse to support a BI solution. This course is a five-day instructor-led course.
Course Price : $2575 Per Participant
Note: This course is retired, Please contact Microtek Learning Consultant or email us at info@microteklearning.com for assistance.
This Data Warehouse With Microsoft SQL Server 2014 training teach you how to implement a data warehouse to support a BI solution.
This course is a five-day instructor-led course. Professional will understand how to create a data warehouse with Microsoft SQL Server 2014, implement ETL with SQL Server Integration Services, and validate and cleanse data with SQL Server Data Quality Services and SQL Server Master Data Services.
Data warehousing is a solution professionals use to centralize business data for reporting and analysis. This course will prepare you for exam 70-463.
This course is for professionals who are interesting in learning SQL Server 2012 or SQL Server 2014.
It includes the new features in 2014 but also the capabilities across the SQL Server data platform.
This training is designed based on the objectives of the course variant 20463D.
Courses
Years of Experience
Global Learners
At least 2 years experience of working with relational databases, including:
An awareness of key business priorities such as revenue, profitability, and financial accounting is desirable.
This course is intended for database professionals who need to fulfill 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. Primary responsibilities include:
Microtek Learning is a Microsoft Certified Partner for Learning Solutions. This class uses official Microsoft courseware and will be delivered by a Microsoft Certified Trainer (MCT).
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You can also speak with a learning consultant by calling 800-961-0337.
This module provides an introduction to the key components of a data warehousing solution and the high-level considerations you must take into account when you embark on a data warehousing project.
Lab: Exploring a Data Warehousing Solution
After completing this module, you will be able to:
This module discusses considerations for selecting hardware and distributing SQL Server facilities across servers.
Lab: Planning Data Warehouse Infrastructure
After completing this module, you will be able to:
This module describes the key considerations for the logical design of a data warehouse, and then discusses best practices for its physical implementation.
Lab: Implementing a Data Warehouse Schema
After completing this module, you will be able to:
This module discusses considerations for implementing an ETL process, and then focuses on Microsoft SQL Server Integration Services (SSIS) as a platform for building ETL solutions.
Lab: Implementing Data Flow in an SSIS Package
After completing this module, you will be able to:
This module describes how to implement ETL solutions that combine multiple tasks and workflow logic.
Lab: Implementing Control Flow in an SSIS Package
Lab: Using Transactions and Checkpoints
After completing this module, you will be able to:
This module describes how you can debug packages to find the cause of errors that occur during execution. It then discusses the logging functionality built into SSIS that you can use to log events for troubleshooting purposes. Finally, the module describes common approaches for handling errors in control flow and data flow.
Lab: Debugging and Troubleshooting an SSIS Package
After completing this module, you will be able to:
This module describes the techniques you can use to implement an incremental data warehouse refresh process.
Lab: Extracting Modified Data
After completing this module, you will be able to:
This module describes the techniques you can use to implement a data warehouse load process.
Lab: Loading a Data Warehouse
After completing this module, you will be able to:
Ensuring the high quality of data is essential if the results of data analysis are to be trusted. SQL Server 2014 includes Data Quality Services (DQS) to provide a computer-assisted process for cleansing data values, as well as identifying and removing duplicate data entities. This process reduces the workload of the data steward to a minimum while maintaining human interaction to ensure accurate results.
Lab: Cleansing Data
Lab: Deduplicating Data
After completing this module, you will be able to:
Master Data Services provides a way for organizations to standardize and improve the quality, consistency, and reliability of the data that guides key business decisions. This module introduces Master Data Services and explains the benefits of using it.
Lab: Implementing Master Data Services
After completing this module, you will be able to:
This module describes the techniques you can use to extend SSIS. The module is not designed to be a comprehensive guide to developing custom SSIS solutions, but to provide an awareness of the fundamental steps required to use custom components and scripts in an ETL process, based on SSIS.
Lab: Using Custom Scripts
After completing this module, you will be able to:
Microsoft SQL Server Integration Services (SSIS) provides tools that make it easy to deploy packages to another computer. The deployment tools also manage any dependencies, such as configurations and files that the package needs. In this module, you will learn how to use these tools to install packages and their dependencies on a target computer.
Lab: Deploying and Configuring SSIS Packages
After completing this module, you will be able to:
This module introduces BI, describing the components of Microsoft SQL Server that you can use to create a BI solution, and the client tools with which users can create reports and analyze data.
Lab: Using a Data Warehouse
After completing this module, you will be able to:
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