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

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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

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

The Federal Republic of Germany is the second most populous country in Europe and is located in Central Europe. The official language of the country is German. Germany is one of the richest countries in the world. The main exports of the country include motor vehicles and iron and steel products.

Here are some fun facts about Germany:
The fairy tale writer, the Brothers Grimm, came from Germany and wrote many famous stories such as Cinderella, Snow White, and Sleeping Beauty.
Germany is home to the largest theme park in Europe, the Europa-Park.
The famous composer Ludwig van Beethoven was born in Germany.
The Autobahn, the German highway system, is known for having no general speed limit.

Berlin was divided by the Berlin Wall from 1961 to 1989. Known for its street art, Berlin has many colorful murals and graffiti throughout the city. Also, Berlin is home to many famous museums, such as the Pergamon Museum and the Museum Island. Many clubs and bars stay open until the early hours of the morning in this big city.

Another popular city is Munich, which is famous for its Oktoberfest beer festival that attracts millions of visitors every year. Munich is also home to many historic buildings, including Nymphenburg Palace and the Marienplatz town square.

The country's capital and largest city is Berlin, however Frankfurt is considered to be the business and financial center of Germany. It is home to the Frankfurt Stock Exchange, the European Central Bank, and many other financial institutions. Because of its central location within Europe and its status as a major financial hub, Frankfurt is often referred to as the "Mainhattan," a play on the city's name and its association with the Manhattan financial district in New York City.

Frankfurt is also a major transportation hub, with the largest airport in Germany and one of the largest in Europe, Frankfurt Airport. Additionally, it is a popular destination for tourists, with its historic city center, beautiful parks, and vibrant cultural scene.

Some of the top German technology companies like Siemens AG, Bosch, SAP SE, Deutsche Telekom, Daimler AG and Volkswagen has business centers in Frankfurt. The country has a strong tradition of engineering and innovation, and is home to many other world-class technology companies and research institutions.

Tailored to meet the specific needs of Germany, Bilginç IT Academy combines cutting-edge training methodologies with our comprehensive range of Certification Exam preparation courses and accredited corporate training programs. Experience a transformative approach to IT training that will redefine your expectations.

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

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

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