TDWI Advanced Data Modeling Techniques Training in Finland

  • Learn via: Classroom / Virtual Classroom / Online
  • Duration: 2 Days
  • Price: Please contact for booking options
We can host this training at your preferred location. Contact us!

Whether you are a business data modeler who represents data requirements as entities and relationships, or a physical data modeler more concerned with tables, columns, and indexes, you know that the hard stuff lies beneath the surface. Every data design, whether logical or technical, is challenged by one or more complex considerations—scalability, adaptability, performance, legacy and package databases, etc. Every data model raises questions. Advanced modeling techniques provide many of the answers. This course explores different situations facing data modeling practitioners and provides information and techniques to help them develop the appropriate data models.

There are no prerequisites for this course.

Data modelers with some practical experience; data architects; database developers

  • Enterprise architecture approaches and how to apply them
  • How big data and analytics impact traditional approaches
  • Different data models and how they relate to each other
  • The role of modeling in analytics
  • Higher normalization forms
  • How to effectively apply generalization and specialization
  • The role of metadata management in data governance
  • State and time dependencies and how to handle them
  • How to validate the data model
  • How to transform the business data model into physical models based on the application
  • The implications of alternative storage approaches
  • The roles and structures of complementary models
  • How to deal with multiple time zones and currencies

Module 1: Data Modeling Concepts

  • Enterprise Architecture
    • Definition
    • Zachman Framework Overview
    • Data Modeling Framework for BI
    • Levels of Data Models – Enterprise Perspective
    • Levels of Data Models – Project Perspective
    • The Open Group Architecture Framework
    • Control Objectives for Information Technology
    • Frameworks – Discussion
  • Higher Normal Forms
    • Boyce-Codd Normal Form
    • Fourth Normal Form
    • Fifth Normal Form
    • Anchor Modeling
    • Data Vault Modeling
  • Specialization and Generalization
    • Roles and Classifications
    • Considerations
    • Party
  • Presentation
    • Standards

Module 2: Business Data Model Development

  • Business Data Model Development Approaches
    • Top-Down
    • Bottom-Up
    • Generic Models
    • Limited Depth Models
  • Data Modeling Roles
    • Functions, Traits, and Challenges
  • Business Data Model Application
    • Basis for System Data Model
    • Transformation and Integration Foundation
    • Package Selection
    • Business Communications
    • Data Profiling
    • Data Governance
  • Data Governance
    • Definition
    • Quality Improvement
    • Real-Time Implications
    • Metadata Management
    • Information Subject Area
    • Big Data
    • Big Data Challenges

Module 3: System and Physical Data Model Development

  • Data Modeling Roles
    • Functions, Traits, and Challenges
  • Globalization / Localization
    • Information Needs
    • Currencies
    • Time Zones
    • Languages
  • Non-Relational Data Structures
    • Columnar Databases
    • In-Memory Databases
    • XML Structures
    • Key Value Pairs
  • Business Analytics
    • Definition
    • Schema on Read
    • Modeling Process

Module 4: Additional Concepts

  • Recursive Relationships
    • Normalized Approach
    • Dimensional Approach
  • Cloud
    • Modeling Implications
  • Complementary Models
    • State Transition Model
    • Function Models
    • Process Models
    • Model Management
  • Model Management
    • Model Validation and Testing
    • Model Synchronization
    • Tool Exploitation
    • Data Modeling Tools
    • Repositories

Module 5: Summary and Conclusions

  • Summary of Key Points
    • A Quick Review
  • Appendix A: Bibliography and References
  • Appendix B: Exercises
    • Exercise 1: Normalization to Higher Normal Forms
    • Exercise 2: Party Modeling
    • Exercise 3: Financial Institution Model
    • Exercise 4: Model Application for Data Profiling
    • Exercise 5: Application System Model Development
    • Exercise 6: Model Evaluation


Contact us for more detail about our trainings and for all other enquiries!

Upcoming Trainings

Join our public courses in our Finland facilities. Private class trainings will be organized at the location of your preference, according to your schedule.

Classroom / Virtual Classroom
12 toukokuuta 2024
Helsinki, Espoo
2 Days
Classroom / Virtual Classroom
25 kesäkuuta 2024
Helsinki, Espoo
2 Days
Classroom / Virtual Classroom
08 heinäkuuta 2024
Helsinki, Espoo
2 Days
Classroom / Virtual Classroom
06 heinäkuuta 2024
Helsinki, Espoo
2 Days
Classroom / Virtual Classroom
16 heinäkuuta 2024
Helsinki, Espoo
2 Days
Classroom / Virtual Classroom
25 heinäkuuta 2024
Helsinki, Espoo
2 Days
Classroom / Virtual Classroom
06 elokuuta 2024
Helsinki, Espoo
2 Days
Classroom / Virtual Classroom
18 elokuuta 2024
Helsinki, Espoo
2 Days
TDWI Advanced Data Modeling Techniques 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.
By using this website you agree to let us use cookies. For further information about our use of cookies, check out our Cookie Policy.