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Supply chain analyticsconcepts, techniques and applications /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Supply chain analyticsby Kurt Y. Liu.
Reminder of title:	concepts, techniques and applications /
Author:	Liu, Kurt Y.
Published:	Cham :Springer International Publishing :2022.
Description:	xix, 377 p. :ill. (chiefly col.), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Business logisticsData processing.
Online resource:	https://doi.org/10.1007/978-3-030-92224-5
ISBN:	9783030922245$q(electronic bk.)

Supply chain analyticsconcepts, techniques and applications /
Liu, Kurt Y.

Supply chain analyticsconcepts, techniques and applications /[electronic resource] :by Kurt Y. Liu. - Cham :Springer International Publishing :2022. - xix, 377 p. :ill. (chiefly col.), digital ;24 cm.

Chapter 1: Introduction -- Chapter 2: Data-drive Supply Chains & Intro to Python -- Chapter 3: Data Manipulation -- Chapter 4: Data Visualization -- Chapter 5: Customer Management -- Chapter 6: Supply Management -- Chapter 7: Warehouse & Inventory Management -- Chapter 8: Demand Management -- Chapter 9: Logistics Management.

This innovative new core textbook, written by an experienced professor and practitioner in supply chain management, offers a business-focused overview of the applications of data analytics and machine learning to supply chain management. Accessible yet rigorous, this text introduces students to the relevant concepts and techniques needed for data analysis and decision making in modern supply chains and enables them to develop proficiency in a popular and powerful programming software. Suitable for use on upper-level undergraduate, postgraduate and MBA courses in supply chain management, it covers all of the major supply chain processes, including managing supply and demand, warehousing and inventory control, transportation and route optimization. Each chapter comes with practical real-world examples drawn from a range of business contexts, including Amazon and Starbucks, case study discussion questions, computer-assisted exercises and programming projects.

ISBN: 9783030922245$q(electronic bk.)

Standard No.: 10.1007/978-3-030-92224-5doiSubjects--Topical Terms:

230874
Business logistics
--Data processing.

LC Class. No.: HD38.5 / .L58 2022

Dewey Class. No.: 658.70285

Supply chain analyticsconcepts, techniques and applications /
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505 0 $a Chapter 1: Introduction -- Chapter 2: Data-drive Supply Chains & Intro to Python -- Chapter 3: Data Manipulation -- Chapter 4: Data Visualization -- Chapter 5: Customer Management -- Chapter 6: Supply Management -- Chapter 7: Warehouse & Inventory Management -- Chapter 8: Demand Management -- Chapter 9: Logistics Management.
520 $a This innovative new core textbook, written by an experienced professor and practitioner in supply chain management, offers a business-focused overview of the applications of data analytics and machine learning to supply chain management. Accessible yet rigorous, this text introduces students to the relevant concepts and techniques needed for data analysis and decision making in modern supply chains and enables them to develop proficiency in a popular and powerful programming software. Suitable for use on upper-level undergraduate, postgraduate and MBA courses in supply chain management, it covers all of the major supply chain processes, including managing supply and demand, warehousing and inventory control, transportation and route optimization. Each chapter comes with practical real-world examples drawn from a range of business contexts, including Amazon and Starbucks, case study discussion questions, computer-assisted exercises and programming projects.
650 0 $a Business logistics $x Data processing. $3 230874
650 0 $a Business logistics $x Management. $3 233497
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