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Data Governance ist kaputt. Es ist Zeit, dass wir es in Ordnung bringen. Warum ist Data Governance so ineffektiv? Die Wahrheit ist, dass Data-Governance-Programme nicht für die Art und Weise entwickelt wurden, wie unsere Data Teams arbeiten. Sie sind nicht für eine moderne Organisation entwickelt worden. Sie wurden entwickelt, als Reports noch über die interne Firmenpost kamen.Der Datenfluss hinein, innerhalb und heraus von heutigen Organisation ist ein Tsunami, der durch starre Data-Governance-Methoden durchbricht. Dennoch verlassen sich unsere Programme auf einen "command und control"-Ansatz. Haben Sie jemals versucht, einen Tsunami zu kontrollieren? Jede Organisation, die Daten verwendet, weiß, dass Sie Data Governance brauchen. Data-Literacy-Anstrengungen und Gesetzgebungen wie die DSVGO sind die Leithammel für unsere Governance-Funktionen geworden. Wir sitzen aber immer noch in Data-Governance-Meetings mit zu geringem Personal und zu vielen Fragen, um voranzukommen. Es gibt nicht genug Agilität für das Programm, weil wir einen Schwächegrad der Daten implizieren, der nicht existiert. Wir setzen unsere Beharrlichkeit auf archaische Methoden fort, die unseren Unternehmen keinen Mehrwert bringen. Wir können keine tiefgehenden Insights in unseren Daten erkennen ohne gute Data-Governance-Praxis.Laura Madsen zeigt Ihnen, wie Sie Governance für das neue Zeitalter neu definieren können. Mit einem lockeren, witzigen Stil tappt Madsen in Ihre jahrzehntelangen Erfahrungen, präsentiert Interviews mit erstklassigen Experten, und begründet Ihre Perspektiven mit Forschungsergebnissen. Seien Sie Zeuge, wie alles zusammengebrochen ist, stellen Sie traditionelle Überzeugungen in Frage, und lassen Sie sich auf eine grundlegende Neueinstellung ein: dass es bei Governance nicht um das Stoppen oder das Vermeiden von Datennutzung geht, sondern um die Unterstützung der Datennutzung. Sie werden es schaffen, Vertrauen und Wert zu Ihren Data-Governance-Funktionen zurückzubringen, und werden über folgendes lernen: - Menschlich-orientierter Ansatz für Governance- Prozesse, die den Datentsunami unterstützen- Moderne Technologien, die Data Governance ermöglichen

The Align > Refine > Design series covers conceptual, logical, and physical data modeling (schema design and patterns) for leading technologies, combining proven data modeling practices with database-specific features to produce better applications. Read Cassandra Data Modeling and Schema Design if you are a data professional who needs to expand your modeling skills to include Cassandra or a technologist who knows Cassandra but needs to grow your schema design skills.The book's introduction and three chapters cover the Align, Refine, and Design approach. We include what the level does in the name by rebranding Conceptual, Logical, and Physical into Align, Refine, and Design. The introduction covers the three modeling characteristics of precise, minimal, and visual; the three model components of entities, relationships, and attributes (including keys); the three model levels of conceptual (align), logical (refine), and physical (design); and the three modeling perspectives of relational, dimensional, and query. Chapter 1, Align, is about agreeing on the common business vocabulary so everyone is aligned on terminology and general initiative scope. Chapter 2, Refine, is about capturing the business requirements. That is, refining our knowledge of the initiative to focus on what is essential. Chapter 3, Design, is about the technical requirements. That is, designing to accommodate our model's unique software and hardware needs.Align, Refine, and Design-that's the approach followed in this book and reinforced through an animal shelter case study. If you are interested in learning how to build multiple database solutions, read all the books in the Align > Refine > Design series. Since each book uses the same template, you can quickly skill up on additional database technologies.

Gouvernance non intrusive des données frappe encore offre un mélange de 50 leçons applicables et de perspectives acquises au cours d'années à aider des organisations du monde entier à suivre l'approche non intrusive, popularisée par le best-seller Gouvernance non intrusive des données.La gouvernance non intrusive des données (GNID) ne signifie pas que la gouvernance des données et des informations sera facile ou sans épreuves. Non intrusif ne signifie pas non plus que le programme n'aura pas d'impact. Le titre de ce livre est une dichotomie : obtenir des résultats mesurables en étant moins menaçant, alors que l'impact de cette approche peut être énorme. Dans la GNID, l'accent est mis sur l'exploitation de le redevabilité existante tout en examinant les possibilités d'amélioration. Ce livre présente un nouveau cadre pour la GNID, qui envisage les principaux éléments d'un programme réussi à travers différentes perspectives de l'organisation.

Apply a step-by-step approach to develop your organization's global data privacy strategy. Data is everywhere. Organizations continuously use data in new ways, often generating cross-border data flows. At the same time, concern about the use of personal data is growing. Every year, more countries adopt data privacy laws and our expectations increase on how companies respect our private data. A data privacy strategy is no longer just about compliance-it is good business. A clear and effective data privacy program can build customer trust and strengthen a brand's reputation. We cover the art of crafting an effective data privacy strategy that aligns with business objectives and brand positioning yet ensures compliance with relevant laws. Gain a foundational understanding of data privacy issues as a prerequisite to developing a custom strategy. Use our review of the major legislations around the world to guide you in creating a data privacy strategy. Benefit from our insights on the relation between data privacy programs and a data strategy, an IT strategy, and risk management frameworks. Be able to apply methodologies to help you stay on track, such as Privacy by Design and data minimization. Incorporate the cultural and ethical considerations of data privacy across different countries where you may operate. Know how emerging privacy enhancing technologies (PETs) can be powerful tools in implementing your strategy, and pinpoint the intersection between data privacy and AI.The stakes for data privacy have never been higher and this book will help you up your game.

The Align > Refine > Design series covers conceptual, logical, and physical data modeling (schema design and patterns) for leading technologies, combining proven data modeling practices with database-specific features to produce better applications. Read Elasticsearch Data Modeling and Schema Design if you are a data professional who needs to expand your modeling skills to include Elasticsearch or a technologist who knows Elasticsearch but needs to grow your schema design skills.The book's introduction and three chapters cover the Align, Refine, and Design approach. We include what the level does in the name by rebranding Conceptual, Logical, and Physical into Align, Refine, and Design. The introduction covers the three modeling characteristics of precise, minimal, and visual; the three model components of entities, relationships, and attributes (including keys); the three model levels of conceptual (align), logical (refine), and physical (design); and the three modeling perspectives of relational, dimensional, and query. Chapter 1, Align, is about agreeing on the common business vocabulary so everyone is aligned on terminology and general initiative scope. Chapter 2, Refine, is about capturing the business requirements. That is, refining our knowledge of the initiative to focus on what is essential. Chapter 3, Design, is about the technical requirements. That is, designing to accommodate our model's unique software and hardware needs.Align, Refine, and Design-that's the approach followed in this book and reinforced through an animal shelter case study. If you are interested in learning how to build multiple database solutions, read all the books in the Align > Refine > Design series. Since each book uses the same template, you can quickly skill up on additional database technologies.

Read true crime stories of people abusing and misusing data. Just because there's data doesn't necessarily mean it's the right data or people are using it properly. And as the saying goes, those who do not learn history are doomed to repeat it. Documenting and understanding these stories can prevent them from happening again. Through a career in data, Merrill sees data problems (data crimes) caused by people treating data improperly. Recognizing data crimes is the first step in getting a resolution. This book details incidents of data crimes and their impact. Although not the person who created the data crime, Merrill can analyze what happened and propose a solution. For people working in data, understanding data crimes and preventing them is essential to your organization. This book gives you specific stories you can share to explain the importance of getting the data right. For people being potential victims of data crimes, awareness will help you steer clear of data crimes, or interact with the offender to come to a resolution. You might finally understand why companies keep making mistakes.

Design and implement a data lakehouse using technology-driven simplifications and generalizations. ¿The approach you will learn enables consolidating even incoherent data from multiple source systems across complex enterprise environments. The precise business question does not need to be known in advance and can even change over time. The approach lends itself well to federated, cooperating data mesh nodes. The individual components, called mini-marts, are like the "data part" of a data quantum and are interoperable. We describe data model blueprints to generalize dimensions with synonyms and facts at different granularities. Includes code examples using complex hierarchies as they exist in heterogenous real-world go-to-market organizations.

The Align > Refine > Design series covers conceptual, logical, and physical data modeling (schema design and patterns) for leading technologies, combining proven data modeling practices with database-specific features to produce better applications. Read Neo4j Data Modeling if you are a data professional who needs to expand your modeling skills to include Neo4j or a technologist who knows Neo4j but needs to grow your schema design skills.The book's introduction and three chapters cover the Align, Refine, and Design approach. We include what the level does in the name by rebranding Conceptual, Logical, and Physical into Align, Refine, and Design. The introduction covers the three modeling characteristics of precise, minimal, and visual; the three model components of entities, relationships, and attributes (including keys); the three model levels of conceptual (align), logical (refine), and physical (design); and the three modeling perspectives of relational, dimensional, and query. Chapter 1, Align, is about agreeing on the common business vocabulary so everyone is aligned on terminology and general initiative scope. Chapter 2, Refine, is about capturing the business requirements. That is, refining our knowledge of the initiative to focus on what is essential. Chapter 3, Design, is about the technical requirements. That is, designing to accommodate our model's unique software and hardware needs.Align, Refine, and Design-that's the approach followed in this book and reinforced through an animal shelter case study. If you are interested in learning how to build multiple database solutions, read all the books in the Align > Refine > Design series. Since each book uses the same template, you can quickly skill up on additional database technologies.

Become proficient in using heuristics within the data science pipeline to produce higher quality results in less time.Although data professionals have used heuristics for many years within optimization-related applications, heuristics have been a vibrant area of research in various data-related areas, from machine learning to image processing. Heuristics also play a role in niche applications such as cybersecurity. In addition, the advent of AI and other data-driven methodologies have brought heuristics to the forefront of data-related work.In this book, we explore heuristics from a practical perspective. We illustrate how heuristics can help you solve challenging problems through simple examples and real-life situations. Apply Jaccard Similarity and a variant, F1 score, Entropy, Ectropy, Area Under Curve, Particle Swarm Optimization, and Genetic Algorithms (along with GA variants). Beyond just exhibiting the various known and lesser-known heuristics available today, we also examine how you can go about creating your own through a simple and functional framework. Code notebooks enable you to practice all of the techniques and explore a few of your own.There is no doubt that the data-driven paradigm is here to stay. There are many ways to stand out in it as a data professional, with AI-related know-how being at the top of the list. However, equally impactful can be the creative tools (heuristics) that make such technologies feasible and scalable. Unfortunately, this is a way that not many people care to follow as it's off the beaten path. Are you up for the challenge?

"A summary of relational theory and relational modeling"--

By "reversing" my diabetes and the progression of coronary heart disease with the positive achievement of weight reduction and general well-being, I have gained knowledge and experience which I want to share with others-for awareness and inspiration. Arjit Mahal.After many years of diligently following the prescribed protocols of medications, procedures, and diet to manage his diabetes and chronic heart disease, Arjit Mahal decided to self-reflect on his healing to gain a deeper understanding of the underlying biological processes of his ailments. Although not having any training in science and medicine, through reading extensively on diabetes, heart disease, blood pressure, and weight gain, he came up with a plan to better health, which he named: Mahal Mantra, Principles & Practices of Healthy Living. His plan included following a plant-based diet, adapting the Ornish Lifestyle Medicine program of multidimensional healing practice, and performing Autophagy-the process of "cleaning out" the damaged components of the body's cells through Fasting. Within 18 months, Arjit's medical profile had a dramatic improvement. His insulin intake became negligible and his heart-related blood numbers normal, and he no longer needed blood pressure medicine. He became more active, alert, and healthier than ever before. This is his story of trial and transformation which takes courage to start, commitment to make it happen, and compliance to sustain the change. Arjit Mahal has written an outstanding book on the utilization of the Dean Ornish diet and Lifestyle wellness program, among other health protocols in treating Type 2 Diabetes Mellitus, Type 1.5 Diabetes Mellitus, Coronary Heart Disease, Obesity, Hypertension, and Hyperlipidemia. This book should be in the hands of all medical students and available in all medical schools. Dr. Francis J. Cinelli, D.O.Pennsylvania, USA

"Learn why the textual warehouse is valuable today, how to build one, and how it compares to the data warehouse"--

Authoritative advice on creating and running a successful API program.The number of articles, books, and documents available on the topic of Application Programming Interfaces (APIs) might lead you to believe the topic has been well researched and well documented. But in fact, confusion abounds, especially about the best ways to create and maintain a successful API program. This book addresses that confusion. It encapsulates years of practical experience on how to make the right decisions at the right times when planning, designing, developing, and marketing APIs. It''s your go-to resource when you want to:Understand how to develop your API program''s business caseDiscover how to best engage your API consumer audienceLearn the best ways to design, build, test, and deploy APIs regardless of technologyImprove the chances of success of your API program over the long haulTechnology will come and go, but the best practices for building an API program are here to stay. Make your journey through the world of APIs a successful one with this book as your experienced guide.Petracek provides an excellent guide on how corporations should leverage an API based service ecosystem to deliver amazing digital customer experiences.-T.M. Ravi, Managing Director, The HiveNelson has taken the complex, technical, arcane, but critical topic of application programming interfaces (APIs) and explained them in a manner that allows the reader and Information Technology practitioner to understand.-Salil Kulkarni, EVP & Interim Chief Information Officer, Caesar''s EntertainmentThis book takes you through everything you need to think about and work through to build an API competency. Each chapter sets out concrete actions for making your program state-of-the-art, and I highly recommend it to anyone involved in that effort.- Maureen Fleming, Program Vice President & Analyst, IDC