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Practical Guide to IT Problem Management

Practical Guide to IT Problem Management

Some IT organisations seem to expend all their energy firefighting – dealing with incidents as they arise and fixing or patching over the breakage. In organisations like this restarting computers is seen as a standard method to resolve many issues. Perhaps the best way to identify whether an organisation understands problem management is to ask what they do after they have restarted the computer. If restarting the computer fixes the issue it is very tempting to say that the incident is over and the job is done. Problem management recognises that things do not improve if such an approach is taken. Such organisations are essentially spending their time running to stay in the same place. Written to help IT organisations move forward Practical Guide to IT Problem Management presents a combination of methodologies including understanding timelines and failure modes drill down 5 whys and divide and conquer. The book also presents an exploration of complexity theory and how automation can assist in the desire to shift left both the complexity of the problem and who can resolve it. The book emphasises that establishing the root cause of a problem is not the end of the process as the resolution options need to be evaluated and then prioritised alongside other improvements. It also explores the role of problem boards and checklists as well as the relationship between problem management and Lean thinking. This practical guide provides both a framework for tackling problems and a toolbox from which to select the right methodology once the type of problem being faced has been identified. In addition to reactive methods it presents proactive activities designed to reduce the incidence of problems or to reduce their impact and complexity should they arise. Solving problems is often a combination of common sense and methodologies which may either be learnt the hard way or may be taught. This practical guide shows how to use problem solving tools and to understand how and when to apply them while upskilling IT staff and improving IT problem solving processes.

GBP 14.99
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Data Analytics and AI

Data Analytics and AI

Analytics and artificial intelligence (AI) what are they good for? The bandwagon keeps answering absolutely everything! Analytics and artificial intelligence have captured the attention of everyone from top executives to the person in the street. While these disciplines have a relatively long history within the last ten or so years they have exploded into corporate business and public consciousness. Organizations have rushed to embrace data-driven decision making. Companies everywhere are turning out products boasting that artificial intelligence is included. We are indeed living in exciting times. The question we need to ask is do we really know how to get business value from these exciting tools? Unfortunately both the analytics and AI communities have not done a great job in collaborating and communicating with each other to build the necessary synergies. This book bridges the gap between these two critical fields. The book begins by explaining the commonalities and differences in the fields of data science artificial intelligence and autonomy by giving a historical perspective for each of these fields followed by exploration of common technologies and current trends in each field. The book also readers introduces to applications of deep learning in industry with an overview of deep learning and its key architectures as well as a survey and discussion of the main applications of deep learning. The book also presents case studies to illustrate applications of AI and analytics. These include a case study from the healthcare industry and an investigation of a digital transformation enabled by AI and analytics transforming a product-oriented company into one delivering solutions and services. The book concludes with a proposed AI-informed data analytics life cycle to be applied to unstructured data. | Data Analytics and AI

GBP 52.99
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