Bøger af Noreen Burlingame

Lars Nielsen and Noreen Burlingame provide a brief, understandable, user-friendly guide to all aspects of Data Science. The authors address the various skills required, the key steps in the Data Science process, software technology related to the effective practice of Data Science, and the best rising academic programs for training in the field. CONTENTS: Data Science Summarized * What is Big Data * Hadoop * Data Management * Data Cleaning * Data Modeling for Unstructured Data * Predictive Analysis * Creativity and Intuition (or Posing the Right Question, at the Right Time, for the Right Data) * Data Visualization (or Telling the Story) * Cassandra * Academic Programs

The need for precise, actionable, real-time Business Intelligence (BI) lies at the heart of the role of Big Data in modern commerce. In turn, the art of "Data Science" lies at the nexus of Big Data and BI, providing the essential methods by which BI can be extracted from Big Data's great black mass of constantly flowing, unstructured information. This combination has a created a new profession: an elite and specialized class of highly-compensated professionals specially skilled at data cleaning, analysis, and visualization. We call them Data Scientists, and their evolving role in the organization is one about which managers must have a clear understanding. As shown in WHAT EVERY MANAGER SHOULD KNOW ABOUT BIG DATA AND DATA SCIENCE, integrating data scientists (and the general practice of Data Science) with the organization is often a delicate process involving the redefinition of traditional roles within the enterprise as well as dealing with issues of territoriality amongst peers. To accomplish this task, managers need a firm knowledge of the what and whys of Data Science, the specific BI needs it is uniquely positioned to service, and the processes by which it functions. Such is the knowledge this important book provides. CONTENTS: Preface The Vital Triangle What Is Big Data?Creativity and Intuition Making Something Out of Nothing Introducing Data Science to the Enterprise Avoiding Friction Between Old & New: Dealing with the TCQ Triangle The Evolving Role of the Data Scientist Data Science Ethics and Privacy Concerns The Art of Seeing ThingsData ManagementArtificial Intelligence, Machine-Learning, and Deep-Learning in Data Science Data Curation and the Tribal Knowledge Problem Data Cleaning Data Modeling for Unstructured Data Predictive Analysis A Bit More On Data Visualization CassandraHadoop Orchestrating Change in the Workplace