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Information resources management.

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This book explains data quality management in practical terms, focusing on three key areas - the nature of data in enterprises, the purpose and scope of data quality management, and implementing a data quality management system, in line with ISO 8000-61.

Information resources management.

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Like other critical organizational assets, information is a strategic asset that requires high level of oversight in order to be able to effectively use it for organizational decision-making, performance improvement, cost management, and risk mitigation. Adopting an information governance program shows a healthcare organization’s commitment to managing its information as a valued strategic asset. Information governance serves the dual purpose of optimizing the ability to extract clinical and business value from healthcare information while meeting compliance needs and mitigating risk. Healthcare organizations that have information governance programs will have a competitive edge over others and contributes to safety and quality of care, population health, operational efficiency and effectiveness, and cost reduction initiatives. This is a much-needed book in the healthcare market space. It will explain, in clear terms, how to develop, launch, and oversee an Information Governance program. It also provides advice and insights from leading IG, cybersecurity and information privacy professionals in healthcare.

Medical informatics. --- Information resources management.

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Management information systems. --- Information resources management.

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Build and deploy data pipelines with Alteryx by applying practical DataOps principles Key Features Learn DataOps principles to build data pipelines with Alteryx Build robust data pipelines with Alteryx Designer Use Alteryx Server and Alteryx Connect to share and deploy your data pipelines Book Description Alteryx is a GUI-based development platform for data analytic applications. Data Engineering with Alteryx will help you leverage Alteryx's code-free aspects which increase development speed while still enabling you to make the most of the code-based skills you have. This book will teach you the principles of DataOps and how they can be used with the Alteryx software stack. You'll build data pipelines with Alteryx Designer and incorporate the error handling and data validation needed for reliable datasets. Next, you'll take the data pipeline from raw data, transform it into a robust dataset, and publish it to Alteryx Server following a continuous integration process. By the end of this Alteryx book, you'll be able to build systems for validating datasets, monitoring workflow performance, managing access, and promoting the use of your data sources. What you will learn Build a working pipeline to integrate an external data source Develop monitoring processes for the pipeline example Understand and apply DataOps principles to an Alteryx data pipeline Gain skills for data engineering with the Alteryx software stack Work with spatial analytics and machine learning techniques in an Alteryx workflow Explore Alteryx workflow deployment strategies using metadata validation and continuous integration Organize content on Alteryx Server and secure user access Who this book is for If you're a data engineer, data scientist, or data analyst who wants to set up a reliable process for developing data pipelines using Alteryx, this book is for you. You'll also find this book useful if you are trying to make the development and deployment of datasets more robust by following the DataOps principles. Familiarity with Alteryx products will be helpful but is not necessary.

Database management --- Information resources management --- Data processing.