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Add to basketPaperback. Condition: new. Paperback. Organizations across industries are embracing data management and governance practices - primarily driven by regulation and value creation by monetization. However, it is important to set up a data office while the firm must ensure the sustenance of such function. Moreover, data governance is a pervasive enabler that supports a firm's corporate governance principles. Tejasvi Addagada, through the book, highlights how an Enterprise can: - Overcome challenges in data offices today - Create a data management strategy and capabilities to traverse data maturity - Set up metadata and data quality management as services - Formalize governance as a function through an operating model, based on an enabling culture - Define a benefits realization model to assess and monitor the value of managing and governing data . This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - You must hear this often if you manage any kind of risk - risk and value go together. And that's true, of course for data! Both data and its infrastructure must be managed for their benefits and risks. The purpose of the book is to elaborate on this need to formalize data risk management. Today, regulations drive enterprises to assess data related risks. Prioritizing and managing data associated with financial or operational risk has been the corner-stone of most regulations like BCBS, CCAR, GDPR to name a few. Nevertheless, data risks can extend beyond regulations to improve existing control environments in companies. By doing so, we will maximize the potential of data capabilities to reach 100%. Through structural alignment within the board and formalizing a data-risk function, the book focuses on managing data risks. Furthermore, the book explains quantitative and qualitative approaches to data risk assessments along with popular tools and techniques. Also, Tejasvi discusses a proven approach to managing data risks called capability-based assessment. As a technique, this can also be applied to data risk planning and formulating a data risk strategy. Twenty data risks and privacy risks are provided in this book by way of examples. These are accompanied by details such as a risk statements, scenarios, causes, and categories of impact if the data risks are to manifest.