TDWI Data Virtualization: Solving Complex Data Integration Challenges (NEW), Finland

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The data integration landscape has changed radically the past few years. What was once a relatively manageable problem of blending and unifying data from enterprise transaction systems has grown to encompass external data, Web data, clickstream data, end-user data, big data, cloud data, and more. New expectations for information-driven business agility further compound the complexities of modern data integration. The ETL-based data warehouse is no longer enough. Data virtualization is a core component of next-generation data integration architectures, techniques, and technology.

Get ready to expand your data integration capabilities, deliver business-speed information, and make the most of recent advances in data integration technology. Through a combination of lecture, exercises, and case study review you will learn how data virtualization works and how to position it in your data integration architecture and processes.

There are no prerequisites for this course.

BI, MDM, and data warehousing program and project managers
Data integration architects, designers, and developers
Data and technology architects

Data virtualization definitions and terminology
Business case and technical rationale for data virtualization
Key concepts and foundational principles of virtualization--views, services, etc.
Data virtualization lifecycle, capabilities, and processes
How to extend the data warehouse with virtualization
How virtualization enables federation and enterprise data integration
How virtualization is applied for big data and cloud data challenges
How companies use virtualization to solve business problems and drive business agility

Data Virtualization Module 1. Data Virtualization Concepts and Principles

Data Virtualization Basics

Data Virtualization Defined
Virtualization vs. Materialization
Virtualization vs. Synchronization
Virtualization vs. Federation
History and Evolution

Why Data Virtualization?

Business Agility
The Data Virtualization Business Case
The Data Virtualization Technical Case

The Data Virtualization Foundation

Views
Query Optimization
Data Services
A “Bird’s-Eye” View

Virtualize or Materialize?

Decision Factors
Business Considerations Discussion

Module 2. Data Integration Architecture

Integration Architecture Concepts

Integration Architecture Defined
Data Sources, Middleware, and Data Consumers
You Have It (Whether Defined or Not)

Reference Architectures

Forrester’s Data Architecture Reference Model
Forrester’s IaaS Architecture
Gartner’s Data Services Layer Architecture
IBM’s BI Reference Architecture

Integration Architecture Examples

Example 1 – Ministry Social Services Logical Architecture
Example 2 – Energy Industry Logical Architecture
Example 3 – Energy Industry Technical Architecture
Example 4 – Financial Services Logical Architecture

Virtualize or Materialize?

Data Source Considerations Discussion

Module 3. Data Virtualization in Integration Architecture

Virtualization in Data Integration Projects

Data Virtualization Use Cases

Data Warehousing Use Cases

Data Warehouse Augmentation
Data Warehouse Federation
Hub and Virtual Spoke
Complement ETL
Data Warehouse Prototyping
Data Warehouse Migration

Data Federation Use Cases

Federated Views
Data Services
Data Mashups
Caches
Virtual Data Marts
Virtual Operational Data Store (ODS)

MDM and EIM Use Cases

Master Data Hub Extension
Master Data Services
Virtual Data Layer
Enterprise Data Services

More Data Virtualization Applications

Virtualization and Big Data
Virtualization and Cloud Data

Virtualize or Materialize?

Data Consumer Considerations Discussion

Module 4. Data Virtualization Platforms

Platform Requirements

Data and Information Services
Development Environment
Management Functions

Platform Capabilities

Access
Delivery
Transformation
Abstraction
Federation
Query Optimization
Caching
Security
Quality
Governance

Platform Variations

Stand-Alone Data Virtualization
Extension of BI or Data Warehousing Platform
Embedded and Appliances
Some Vendors

Module 5. Implementing Data Virtualization

Analysis

Goals and Purpose
Scoping
Data Source Discovery
Source Data Analysis

Design and Modeling

Data Source Layer
Data Integration Layer
Publish and Access Layer

Development

Connect to Data Sources
Build the Views
Test and Validate
Publish and Connect Applications

Deployment

Acceptance Testing and Production

Operation

Runtime Operations
Management and Governance

Virtualize or Materialize?

A Decision Tool

Module 6. Getting Started with Data Virtualization

Skills and Competencies

Capabilities and Expertise

Human Factors

People and Data Virtualization

Goals and Expectations

DV Readiness
Choosing a First DV Project
Planning a DV Roadmap

Best Practices

What Works in DV
Mistakes to Avoid

Why have you chosen us?

I have attended a training from Bilginc IT Academy before and I was satisfied.

I have attended a training from a different provider and it was not helpful.

Other

How many employees do you have in your IT department?

0 – 50

50 – 250

250 – 1000

1000+

TDWI Data Virtualization: Solving Complex Data Integration Challenges (NEW) Training Course in Finland

Finland is a country located in northern Europe. Helsinki is the capital and largest city of the country. The majority of the people are Finns but there is also a small Lapp population in Lapland, where the country is famous for the Northern Lights. Finland's national languages are Finnish and Swedish.

Known for its vast forests, lakes, and natural beauty, Finland is one of the world's largest producers of forest products, such as paper, pulp, and lumber. One of the world's largest sea fortresses Suomenlinna, Rovaniemi with the "White Nights", dogsled safaris and of course the Northern Lights are what makes Finland so popular for tourists. Finland is one of the best places in the world to see the Northern Lights and attracts millions of tourists during its seasons.

Finland is home to a thriving technology industry and is widely recognized as one of the world's leading technology hubs. Companies such as Nokia and Rovio (creator of the popular game Angry Birds) are based in Finland. Some of the key factors that have contributed to Finland's success in technology include; strong investment in research and development, a highly educated workforce and fundings.

Finland has a strong educational system, and is widely regarded as one of the world's most literate countries. In fact, Finland's literacy rate is one of the highest in the world, and its students consistently perform well in international tests of math and reading ability.

Also, as a pioneer in environmental sustainability, Finland is known for its efforts to reduce its carbon footprint and promote clean energy. This Nordic country is also famous for its unique and distinctive cultural heritage, including its traditional folk music and its elaborate traditional costumes.

Helsinki, Finland's capital city, is the country's business center. Helsinki is Finland's largest city, and it is home to many of the country's major corporations and organizations, including many of the country's leading technology firms. The city is also a commercial, trade, and financial center, as well as one of the busiest ports in the Nordic region.

Take advantage of our diverse IT course offerings, spanning programming, software development, business skills, data science, cybersecurity, cloud computing and virtualization. Our knowledgeable instructors will provide you with practical training and industry insights, delivered directly to your chosen venue in Finland.

TDWI Data Virtualization: Solving Complex Data Integration Challenges (NEW) Training in Finland

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TDWI Data Virtualization: Solving Complex Data Integration Challenges (NEW) Training in Finland

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