IT is characterized by innovations and rapid changes. Sustainability, and with it the interests of the next generation, has not been as much of a focal point so far. However, in order to achieve the ambitious climate targets, the IT sector, as an important driver of digitization, has to make its contribution as well. An intelligent use of resources to avoid waste and litter is a start here. The experience gained in economical energy consumption on a large scale in the cloud, but also on a small scale in the embedded sector, can also be useful for companies. I present some aspects that have received too little attention as of yet and how one can improve one’s climate footprint by switching to a “green cloud” and other processor architectures. Thereby, the competing interests of economy and ecology can be better combined.
Natural language processing (NLP) has made incredible strides in the past few months. With these new possibilities and more and more textual data, we will see an increasing demand for NLP-based development. We have built several NLP-based systems in productive quality over the past eight years. It didn’t always go completely smoothly and the product didn’t always deliver what we wanted to achieve in the end. In this lecture we would like to report on our experiences: 1. What are the use cases of text analytics? 2. Which specific information can be extracted from text using NLP libraries? 3. What are the limits of text analytics? This talk should encourage to deal with NLP but at the same time slow down the current euphoria and expectations.
Our hope is that anyone looking to embark on a legacy modernisation programme or who is currently involved with one will find some useful advice here. We have spent most of the last couple of decades helping large organizations overhaul their legacy systems. In doing this we’ve learned a great deal about what works and seen many paths that lead to failure. In this talk we describe several of the legacy supplanation patterns that we found to be successful as well as some of the “anti-patterns” that more often than not lead to failure. For each pattern, we describe a particular approach, the context where it’s effective and explain how and why you might use them, giving real world examples along the way. Key to our approach is seeing legacy replacement as a holistic activity that cuts across technology, business processes and organisation structure. In more detail using these patterns often means discovering how one large technical solution meets multiple business needs and then seeing if it is possible to extract individual needs for independent delivery using a new solution. We describe how different elements of current solutions might be mapped to business capabilities and, using examples, how the various patterns can then be used to incrementally deliver these replacement solutions over time. A common objection is that finding these “seams” in existing systems is too difficult. While we agree it is challenging at first, we have found it to be a better approach than the alternatives which all too often result in Feature Parity and Big Bang releases. We describe these anti-patterns as well as some of the underlying organisational reasons many legacy replacement programmes fail. This talk is drawn from material being produced in collaboration with Martin Fowler and James Lewis which will be published in the coming months on Martin’s site.