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Practical Guidelines for Designing New Data Architectures

Ari Hovi Oy
2 days
1 900 EUR excl. VAT
Nationwide, Verkossa
Start dates
Yrityskohtaisesti sopimuksen mukaan

1 900 EUR

Practical Guidelines for Designing New Data Architectures

Digital transformation, the data-driven organization, and the ‘data economy’ are popular topics in boardrooms today. Regardless of what these terms exactly mean, it means that organizations want to do more with data. Data has to be deployed more widely, more efficiently, and more effectively to improve their business and decision-making processes and to increase their competitive power. Technically, this implies that new forms of data usage must be deployed, such as data science, self-service BI, embedded BI, edge analytics, and customer-driven BI.

Current challenges

Unfortunately, current IT systems such as the data warehouse and the transactional systems, can no longer cope with these new, more intense, and resource-intense forms of data usage. The current data architecture for data delivery is already overstretched. Some of these systems are over twenty years old and many changes and extensions have been applied. They can’t process the ever-increasing workload. Additionally, because they have become static and inflexible, implementing new reports and executing new forms of analytics have become very time consuming. In other words, the current data-architecture can’t cope with today’s current ‘speed of business change’.

The effect is that, understandably, countless organizations have decided to develop a new and future-proof data architecture. However, this is easier said than done. You don’t design data architectures every day.  Which new technologies are available today? What is the influence of new technologies on the architecture, such as Hadoop, NoSQL, big data, data warehouse automation, and data-streaming? Which new architectural  principles should be applied? How do we handle the new rules and regulations for data storage and analysis? And what is the influence of cloud platforms?

Learn practical tips, experiences, guidelines, do’s and don’ts

This two-day seminar answers most of the common questions architects have when designing a modern data architecture. This is done through guidelines, tips, and design rules. Concepts and technologies, such as data lakes, big data, datavault, cloud, data virtualization, Hadoop, NoSQL, data warehouse automation, and anonymization of data are discussed. The seminar is based on practical experiences while designing and implementing modern data architectures. Also, the relationship between a modern data architecture and more organizational aspects are addressed as well, including data quality, data governance, data strategy, and the migration to a new architecture.

Main Topics

  • Part 1: Introduction – what is a data architecture?
  • Part 2: Overview of new technologies for data storage, data processing, and data analytics
  • Part 3: Design aspects of data architectures
  • Part 4: Innovating new data architectures
  • Part 5: Action plan for developing a complete and correct data architecture

Want to know more?

For more information about Practical Guidelines for Designing New Data Architectures, please submit an information request below and the school will contact you with further information.



Rick van der Lans is a highly-respected independent analyst, consultant, author, and internationally acclaimed lecturer specializing in data architectures, data warehousing, business intelligence, big data, and database technology. In 2018 he was selected the sixth most influential BI analyst worldwide by

He has presented countless seminars, webinars, and keynotes at industry-leading conferences. He also helps clients worldwide to design their data warehouse, big data, and business intelligence architectures and solutions and assists them with selecting the right products.


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