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?