03020nam 22006254a 450 991078026930332120221206193811.01-62198-341-20-8144-2932-7(CKB)111086906305794(CtWfDGI)bkb00001785(SSID)ssj0000079276(PQKBManifestationID)11188510(PQKBTitleCode)TC0000079276(PQKBWorkID)10068019(PQKB)10120279(Au-PeEL)EBL3001760(CaPaEBR)ebr10057971(CaONFJC)MIL928791(OCoLC)56072883(CaSebORM)9780814429327(MiAaPQ)EBC3001760(EXLCZ)9911108690630579420030926d2004 uy 0engurzn||||||txtccrThe art of winning commitment[electronic resource] 10 ways leaders can engage minds, hearts, and spirits /Dick Richards1st editionNew York AMACOMc2004x, 212 p. illTitle from title screen.0-8144-0785-4 Includes bibliographical references and index.Leadership books most often cite interviews with high-profile business executives while offering do-and-don’t case studies of different corporate initiatives in action. But some of the world’s most extraordinary leaders work their magic outside the world of business. Their ability to gain the enthusiastic commitment of their people -- when something other, and perhaps greater, than profit is at stake -- demonstrates a fundamental human connection that their counterparts in the corporate sector would do well to emulate. The Art of Winning Commitment presents the unique perspectives of a diverse group of leaders that includes: * educators * religious and spiritual leaders * heads of not-for-profit social services * an orchestra conductor * a professional storyteller Readers will also learn leadership secrets from former Philadelphia 76ers’ executive Pat Croce, former Chief of the Cherokee Nation Wilma Mankiller, and politician and retired U.S. Army General Wesley Clark, and others. In the search for commitment, loyalty, and business excellence, leaders can learn a lot from those outside of the business definition of leadership.10 ways leaders can engage minds, hearts, and spiritsCommitment (Psychology)Employee loyaltyEmployee motivationOrganizational commitmentCommitment (Psychology)Employee loyalty.Employee motivation.Organizational commitment.658.3/14Richards Dick1943-1503316MiAaPQMiAaPQMiAaPQBOOK9910780269303321The art of winning commitment3731614UNINA03602oam 22005412 450 991079993410332120200526015934.01-000-39824-21-000-43908-90-429-32173-2(CKB)4100000011210034(MiAaPQ)EBC6191843(OCoLC)1114498339(OCoLC-P)1114498339(FlBoTFG)9780429321733(EXLCZ)99410000001121003420190901d2020 uy 0engurun|||||||||txtrdacontentcrdamediacrrdacarrierBig data with Hadoop MapReduce a classroom approach /Rathinaraja Jeyaraj, Ganeshkumar Pugalendhi, Anand PaulBurlington, ON, Canada ;Palm Bay, Florida, USA :Apple Academic Press,2020.1 online resource (427 pages)1-77188-834-2 Big Data -- Hadoop Framework -- Hadoop 1.2.1 Installation -- Hadoop Ecosystem -- Hadoop 2.7.0 -- Hadoop 2.7.0 Installation -- Data Science."The authors of Big Data with Hadoop MapReduce: A Classroom Approach have framed the book to facilitate understanding big data and MapReduce by visualizing the basic terminologies and concepts. They employed over 100 illustrations and many worked-out examples to convey the concepts and methods used in big data, the inner workings of MapReduce, and single node/multi-node installation on physical/virtual machines. This book covers almost all necessary information on Hadoop MapReduce for most online certification exams. Upon completing this book, readers will find it easy to understand other big data processing tools such as Spark, Storm, etc. Ultimately, readers will be able to: understand what big data is and the factors that are involved, understand the inner workings of MapReduce, which is essential for certification exams, learn the MapReduce program's features along its weaknesses, set up Hadoop clusters with 100s of physical/virtual machines, create a virtual machine in AWS and set up Hadoop MapReduce, write MapReduce with Eclipse in a simple way, understand other big data processing tools and their applications, understand various job positions in data science, regardless of the user's domain and expertise level in Hadoop MapReduce, this volume will broaden their knowledge and understanding of writing MapReduce programs to process big data. The authors advise that while it is not necessary to be an expert, readers should have some minimal knowledge of working in Ubuntu, Java, and Eclipse to set up clusters and write MapReduce jobs. The authors have emphasized more on Hadoop v2 when compared to Hadoop v1, in order to meet today's trend."--Provided by publisher.Big dataFile organization (Computer science)COMPUTERS / Database Management / GeneralbisacshCOMPUTERS / Information TechnologybisacshCOMPUTERS / Management Information SystemsbisacshBig data.File organization (Computer science)COMPUTERS / Database Management / GeneralCOMPUTERS / Information TechnologyCOMPUTERS / Management Information Systems004.36Jeyaraj Rathinaraja1586731Pugalendhi GaneshkumarPaul AnandOCoLC-POCoLC-PBOOK9910799934103321Big data with Hadoop MapReduce3873589UNINA