Big Data Management (Over 2,100 results)

Paperback. Condition: Fair. 1. The item might be beaten up but readable. May contain markings or highlighting, as well as stains, bent corners, or any other major defect, but the text is not obscured in any way. Markings in workbook.

Hardcover. Condition: Good. 1st Edition. Ships same day or next business day! UPS shipping available (Priority Mail for AK/HI/APO/PO Boxes). Used sticker and some writing and/or highlighting. Used books may not include working access code. Used books will not include dust jackets.

Hardcover. Condition: Good. ARRIVES IN 2-4 BUSINESS DAYS if you choose Expedited Shipping! Orders ship the same or next business day. All orders ship with a tracking number.Access codes and supplements are not guaranteed to be included with used books. Ships same or next day. Expedited shipping: 3-5 business days, Standard shipping: 4-14 business days.…

Paperback. Condition: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

Paperback. Condition: Fair. Book in Fair condition.

Paperback. Condition: Good. Book in Good condition.

Condition: Very Good. Dust Jacket Condition: 47408505. 1763558712. 11/19/2025 1:25:12 PM.

Softcover. Condition: Très bon. Ancien livre de bibliothèque avec équipements. Edition 2017. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Very good. Former library book. Edition 2017. Ammareal gives back up to 15% of this item's net price to charity organizations. …

Softcover. Condition: Bon. Ancien livre de bibliothèque avec équipements. Edition 2017. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Good. Former library book. Edition 2017. Ammareal gives back up to 15% of this item's net price to charity organizations.…

Condition: New.

Condition: As New. Unread book in perfect condition.

Paperback. Condition: Good. Entity Information Life Cycle for Big Data walks you through the ins and outs of managing entity information so you can successfully achieve master data management (MDM) in the era of big data. This book explains big data?s impact on MDM and the critical role of entity information management system (EIMS) in successful MDM. Expert authors Dr. John R. Talburt and Dr. Yinle Zhou provide a thorough background in the principles of managing the entity information life cycle and provide practical tips and techniques for implementing an EIMS, strategies for exploiting distributed processing to handle big data for EIMS, and examples from real applications. Additional material on the theory of EIIM and methods for assessing and evaluating EIMS performance also make this book appropriate for use as a textbook in courses on entity and identity management, data management, customer relationship management (CRM), and related topics.…

Condition: Very Good. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Paperback or Softback. Condition: New. Big Data Management and Analytics. Book.

Condition: New.

Paperback or Softback. Condition: New. Digital Transformation in Water: Supporting Water Conservation, Smart Water Management, Big Data, IoT, Cloud Platforms, and AI Solutions. Book.

Condition: New.

Paperback or Softback. Condition: New. Obtaining Value from Big Data for Service Systems, Volume I: Big Data Management. Book.

Softcover. Condition: Très bon. Ancien livre de bibliothèque avec équipements. Edition 2016. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Very good. Former library book. Edition 2016. Ammareal gives back up to 15% of this item's net price to charity organizations. …

Softcover. Condition: Très bon. Ancien livre de bibliothèque avec équipements. Edition 2016. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Very good. Former library book. Edition 2016. Ammareal gives back up to 15% of this item's net price to charity organizations. …

Paperback. Condition: Good. Entity Information Life Cycle for Big Data walks you through the ins and outs of managing entity information so you can successfully achieve master data management (MDM) in the era of big data. This book explains big data?s impact on MDM and the critical role of entity information management system (EIMS) in successful MDM. Expert authors Dr. John R. Talburt and Dr. Yinle Zhou provide a thorough background in the principles of managing the entity information life cycle and provide practical tips and techniques for implementing an EIMS, strategies for exploiting distributed processing to handle big data for EIMS, and examples from real applications. Additional material on the theory of EIIM and methods for assessing and evaluating EIMS performance also make this book appropriate for use as a textbook in courses on entity and identity management, data management, customer relationship management (CRM), and related topics.…

Paperback. Condition: Good. Comprehensively covers evaluation criteria for and capabilities of the software tools available for implementing a data governance program   Data governance programs often start off using programs such as Microsoft Excel and Microsoft SharePoint to document and share data governance artifacts. But these tools often lack critical functionality. Meanwhile, vendors have matured their data governance offerings to the extent that today's organizations need to consider tools as a critical component of their data governance programs. In this book, data governance expert Sunil Soares reviews the Enterprise Data Management (EDM) reference architecture and discusses key data governance tasks that can be automated by tools for business glossaries, metadata management, data profiling, data quality management, master data management, reference data management, and information policy management. Subsequent sections describe the integration points between EDM tools and data governance and examine how governance tools interact with big data technologies, including Hadoop, NoSQL, stream computing, and text analytics. The final section of the book discusses evaluation criteria for data governance tools and provides an overview of key vendor platforms, including ASG, Collibra, Global IDs, IBM, Informatica, Orchestra Networks, SAP, and Talend.…

Paperback. Condition: Very Good.

Condition: very good. Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages.

Condition: as new. Wie neu/Like new.

Paperback. Condition: Good. Data Management - Data Modeling - Database Languages - Ensuring Data Consistency - System Architecture - Post-Relational Databases - NoSQL Databases.

Condition: As New. Unread book in perfect condition.

Condition: As New. Unread book in perfect condition.

Paperback. Condition: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

Paperback. Condition: Good. Comprehensively covers evaluation criteria for and capabilities of the software tools available for implementing a data governance program   Data governance programs often start off using programs such as Microsoft Excel and Microsoft SharePoint to document and share data governance artifacts. But these tools often lack critical functionality. Meanwhile, vendors have matured their data governance offerings to the extent that today's organizations need to consider tools as a critical component of their data governance programs. In this book, data governance expert Sunil Soares reviews the Enterprise Data Management (EDM) reference architecture and discusses key data governance tasks that can be automated by tools for business glossaries, metadata management, data profiling, data quality management, master data management, reference data management, and information policy management. Subsequent sections describe the integration points between EDM tools and data governance and examine how governance tools interact with big data technologies, including Hadoop, NoSQL, stream computing, and text analytics. The final section of the book discusses evaluation criteria for data governance tools and provides an overview of key vendor platforms, including ASG, Collibra, Global IDs, IBM, Informatica, Orchestra Networks, SAP, and Talend.…