Ten practical guidelines for modern data architectures (Dutch spoken)

Many IT systems are more than twenty years old and have undergone numerous changes over time. Unfortunately, they can no longer cope with the ever-increasing growth in data usage in terms of scalability and speed. In addition, they have become inflexible, which means that implementing new reports and performing analyses has become very time-consuming. In short, the data architecture can no longer keep up with the current “speed of business change”. As a result, many organizations have decided that it is time for a new, future-proof data architecture. However, this is easier said than done. After all, you don’t design a new data architecture every day. In this session, ten essential guidelines for designing modern data architectures are discussed. These guidelines are based on hands-on experiences with designing and implementing many new data architectures.

• Which new technologies are currently available?
• What is the influence on the architecture of e.g. Hadoop, NoSQL, big data, data warehouse automation, and data streaming?
• Which new architecture principles should be applied nowadays?
• How do we deal with the increasingly paralyzing rules for data storage and analysis?
• What is the influence of cloud platforms?