Practical Guidelines for Designing Modern Data Architectures

by Rick van der Lans download a PDF brochure

Description

Digital transformation, the data-driven organization, and the ‘data economy’ are popular topics in boardrooms today, because organizations understand the need to do more with data. They want to make use of the strengths and benefits of data science, self-service BI, embedded BI, edge analytics, and customer-driven BI.

The consequence is that data needs to be deployed more widely, more efficiently, and more effectively. Unfortunately, current IT systems, such as the data warehouse and transactional systems, can no longer cope with the ever-increasing workload. They have already been overstretched.

For many organizations it’s time for a new and future-proof data architecture.

But designing new data architectures is not something you do every day. This two-day seminar answers through guidelines, tips, and design rules many common questions raised when designing a modern data architecture.

Concepts and technologies, such as Data Lakes, Big Data, Data Vault, Cloud, Data Virtualization, Hadoop, NoSQL , and Data Warehouse automation, are explained. The seminar is based on practical experiences while designing and implementing modern data architectures for numerous organizations.

What you will learn

What are the steps to take to come up with the perfect data Architecture? From requirement analysis via proof of concepts to a data Architecture
What is the importance of a holistic approach to analyzing technology, organization, and architecture in conjunction?
What are real life examples of new data Architectures?
How can the new technology use optimally within a new data Architecture?
How do you develop a data Architecture?
Which components make up a data Architecture?
What are the use cases, pros and cons of new technologies and how do they influence data Architectures?
What is the value of well-known reference architectures, such as the Lambda Architecture, the Logical Data Warehouse Architecture and the Data Lake?
What are the right criteria for a data Architecture?

Main Topics

Introduction - what is a Data Architecture?
Overview of new technologies for data storage, data processing, and data Analytics
Design aspects of data Architectures
Innovating new data Architectures
Action plan for developing a complete and correct data Architecture