Implementing a Data Warehouse with Microsoft SQL Server (M20463) | MSP Training

ABOUT THE PROGRAM

The course provides the essential knowledge to implement a data warehouse platform to support a business intelligence solution. The 5-day course covers the crucial capabilities across the SQL Server data platform and discusses new components of SQL Server 2014. During the course, the delegates will learn how to create a data warehouse, extract and transform data, configure SQL Server Integration Services and deploy SQL Server Master Data Services and Data Quality Services.

The course is specifically designed for database administrators and professionals who are responsible for creating and supporting data warehousing solution within an organization. The course teaches delegates to support incremental data extraction and data loading by implementing extracting, transforming and loading (ETL) process. After the completion of the course, the delegates will be able to create business intelligence solutions, implement data warehouse and data cleansing and validating effectively.

Deploy and Configure SSIS packages effectively
Enforce data integrity using SQL Server Data Quality Services
Managing consistency by implementing ETL solutions
Manage and monitor the execution of deployed packages
Courses led by highly certified and well experienced Microsoft Server Instructors

WHAT'S INCLUDED ?

Find out what's included in the training programme.

Tutor Support

A dedicated tutor will be at your disposal throughout the training to guide you through any issues.

Key Learning Points

Clear and concise objectives to guide delegates through the course.

Exam(s) included

Exams are provided, as part of the course. Obtaining certification is dependant on passing these exams

Certificate

Delegates will get certification of completion at the end of the course.

PREREQUISITES

The delegates must have at least two years of working experience with relational databases. These include:

Designing tables and relationships
Querying with Transact-SQL
Creating a normalized database
Having knowledge of key business priorities and basic programming constructs

TARGET AUDIENCE

The course is intended for database administrators and professionals responsible for:

Designing SQL Server integration service package for extracting, loading and transforming data
Apply data quality services for cleansing data
Implementing a data warehouse
Use master data services for administering data integrity

WHAT WILL YOU LEARN?

Understand concepts and basic architecture of data warehouse
Able to design and implement a data warehouse
Describe an appropriate hardware platform for a data warehouse
Get to know the configuration of SSIS packages
Learn how to implement data flow and control flow in SSIS Package
Explain debugging and troubleshooting of SSIS packages
Describe how Microsoft data quality services use for data cleansing and validating
Understand SSIS expansion with custom scripts and components
Learn to implement a SSIS solution supporting extracting data and incremental data warehouse loads
Learn to enforce data integrity by implementing master data services
Describe how business intelligence solutions consume data in a data warehouse

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PROGRAM OVERVIEW

The course enables the delegates to implement an ETL solution that supports incremental data extraction and data loading. The course provides an opportunity to learn the key components and considerations of a data warehousing project and describes common approaches for handling errors in data flow and control flow. Throughout the course, the delegates will learn how to design and implement a data warehouse, deploy and configure SSIS packages and implement control flow and data flow in server integration packages.

Important information on implementing a Data Warehouse with Microsoft SQL Server exam

The course prepares the delegates to enable them to sit in the examination and cover the following aspects:

Design and Implement a Data Warehouse
Data loading
Extract and transform data
Deploy and configure SSIS Solutions
Building data quality solutions

PROGRAM CONTENT

An Introduction to Data Warehousing

In this module, while undertaking data warehousing projects one must take into account the key components of data warehousing and other high-level considerations of SQL Server.

Overview of data warehousing
Understand its basic architecture
Understand the key elements of a data warehousing solution
Describe considerations for data warehousing solution

Planning Data Warehouse Infrastructure

In this module, the delegates will identify the parameters to consider for selecting data warehouse hardware and distributing SQL Server facilities across servers.

Considerations for Data Warehousing Infrastructure
Data Warehouse Reference Architectures and Appliances
Planning Data Warehouse Hardware

Design and implement Data Warehouse

The topic covers understanding about key factors for the logical design of data warehouse and then discuss best practices for physical implementation.

Overview of Data Warehouse design
Design dimension tables
Design fact tables
Physical design for data warehouse
Design and implement effective physical data structures

Create an ETL solution with SSIS

This topic elaborates considerations for implementing ETL process and then focus on Microsoft SQL Server Integration Services (SSIS) for building ETL solutions.

Understand process of ETL with SSIS
Describe key features of SSIS
Use SSIS for implementation of data flow
Explore data sources

Implementing Control Flow in a SSIS package

In this module, the delegates learn how to implement ETL solutions that consolidate multiple tasks and workflow logic.

Introduction to control flow
Use of task constraints to execute control flow
Develop dynamic packages including parameters and variables
Use containers in a package control flow
Techniques to manage consistency with checkpoints and transactions

Debugging and troubleshooting SSIS packages

This module discusses how you can debug packages to find the reason of errors occur during execution and also understand the logging functionality built into SSIS that can be used to log events for troubleshooting purposes. The delegates also get familiar with the basic approaches for handling errors in control flow and data flow.

Describe Debugging of a SSIS package
Logging SSIS package events
Techniques to handle errors in SSIS package

Implementing a Data Extraction Solution

This module covers the techniques that can be used to perform an incremental data warehouse refresh process.

Overview of Incremental ETL
Plan data extraction
Loading modified data

Loading data into Data Warehouse

In this module, the techniques used to implement data warehouse load process is covered.

Plan data loads
Use SSIS for incremental loads
Use Transact-SQL loading techniques

Enforce Data Quality

This module covers Microsoft SQL Server Data Quality Services (DQS) and describes how it can be used to cleanse and de-duplicate data.

Understand importance of Data Quality
Overview of Microsoft SQL Server Data Quality Services (DQS)
Using data quality services for cleansing and validating

Master data Services

This module describes how Master Data Services provides a way for organizations to standardize data and improve its quality, consistency, and reliability that helps in key business decisions. It also explains Master Data Services and its advantages of applying it.

Introduction to Master Data Services concepts
Implement Master Data Services model
Manage Master data
Create Master data hub

Extending SQL Server Integration services

This module covers the techniques to extend SSIS and also provide awareness of major steps required to use scripts in an ETL process and custom components based on SSIS.

Include custom scripts in SSIS package
Use custom components in SSIS to extend SSIS

Deploy and configure SSIS packages

The topics cover how to implement packages and their dependencies to the server.

Describe key elements of SSIS deployment
Deploy SSIS projects
Plan SSIS package execution
Monitor the implementation of deployed packages

Consuming Data in Data Warehouse

This module describes Business Intelligence solutions that data warehouse can use as a basis for enterprise and self-service BI lessons.

Understand BI and common scenarios of BI
Enterprise Business Intelligence
Describe reporting
Overview of data analysis
Big data and Self-Service BI

Implementing a Data Warehouse with Microsoft SQL Server (M20463) Enquiry

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ABOUT London

London, also known as Greater London is the capital city of the United Kingdom with a population of around 9787426 according to 2011 census. It is the most populous city in the country and located on the Thames River towards the south-east of the Great Britain. The city is also referred as metropolis around the ancient core and Greater London which comprises Surrey, Middlesex, Hertfordshire, Essex, and Kent regulated by the London Assembly. In the era of globalisation, the city is crowned as a leading centre in the fields of education, infrastructure, healthcare, tourism, entertainment and professional services.

History

The history of the city traced its roots back to the Roman period and Romans named it Londinium. Recently, two discoveries found on the south bank near the Thames River showing the remains of Bronze Age Bridge gave access to a lost island in the river and foundations of large timber structure situated on Thames foreshore. The walled city of London was abandoned with the downfall of the Roman rule during the fifth century and new settlement Lundenwic was developed to the west of the old city. The city became a major port and established Danelaw in the Vikings period. The city developed dramatically after the abandonment of Lundenwic and became the largest town and trading centre of the country.

The population of the city grew from 18000 to approx. 100,000 by the end of 13^th century and became England’s principal commercial and administrative centre. The focus of the city changed to private ownership with the establishment of exchange, mercantile and trading companies during the Tudor period. The city was severely affected by Great Plague disease resulted in the death of 100,000 people and also faced destruction in the large parts of the city with the great fire of London. The city also remained as the largest city in the world till 1925. London was the prime target by German bombers during the First and Second World War, destroyed many residential projects and commercial buildings across the city. In 1948, Summer Olympics were held in the city and attracted a large number of immigrants from Commonwealth countries.

Architecture

With the presence of various diverse buildings with varying ages, the walled city cannot be represented by any specific architectural style. Few structures in the central London including Tower of London, National Gallery, and Hampton Court Palace were constructed during Roman and Tudor period. While other famous buildings include churches and financial institutions that represent the modern architecture and formed part of the varied architectural heritage. Central London has some tall skyscrapers including the tallest building in the European Union and older buildings decorated with beautiful carvings and white plaster mouldings. The other famous buildings of the city are British Library, City Hall, and Millennium Dome.

Religion

The majority of the population of the city follows Christianity followed by Muslims, Hindus, Sikhs, Jews, and Buddhists. A large number of churches and well-known cathedrals are constructed in the city including Southwark Cathedral and St Paul’s Cathedral. Muslim communities are largely based in the boroughs of Newham and Tower Hamlets and famous mosques in the city are London Central Mosque, East London Mosque, and Baitul Futuh Mosque. There are approximately 42 Hindu temples in the city and Hindu communities are mainly settled in the Harrow and Brent boroughs.

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The city is ranked among the leading tourist destinations in the world and crowned top city destination by Trip Advisor users. The notable buildings of the city are Natural History Museum, The British Museum, Tate Modern, Science Museum, Tower of London, Southbank Centre, National Portrait Gallery and many more exciting attractions.

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