000			03785cam a2200361Ia 4500
003			OCoLC
005			20220922112516.0
020			_a9780124059207
020			_a0124059201
020			_a0124058914
020			_a9780124058910
020			_z9780124058910 _q(pbk.)
040			_aUMI _beng _epn _cUMI _dCNNAI _dOCLCO _dB24X7 _dDEBSZ _dDKDLA _dOCLCQ _dOCLCF _dOCLCQ _dCEF _dAU@
041			_aEng
050		4	_aQA76.9.D37
100	1		_aKrishnan, Krish _eAuthor
245	1	0	_aData warehousing in the age of big data / _cKrish Krishnan _hTextbook
260			_aWaltham, MA : _bMorgan Kaufmann, _c2013
300			_ax1x,335pages,: _billustrations _c25 cm
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
504			_aIncludes bibliographical references and index
505	0		_aPart 1 -- Big Data Chapter 1 -- Introduction to Big Data Chapter 2 -- Complexity of Big Data Chapter 3 -- Big Data Processing Architectures Chapter 4 -- Big Data Technologies Chapter 5 -- Big Data Business Value Part 2 -- The Data Warehouse Chapter 6 -- Data Warehouse Chapter 7 -- Re-Engineering the Data Warehouse Chapter 8 -Workload Management in the Data Warehouse Chapter 9 -- New Technology Approaches Part 3 -- Extending Big Data into the Data Warehouse Chapter 10 -- Integration of Big Data and Data Warehouse Chapter 11 -- Data Driven Architecture Chapter 12 -- Information Management and Lifecycle Chapter 13 -- Big Data Analytics, Visualization and Data Scientist Chapter 14 -- Implementing The "Big Data" Data Warehouse Appendix A -- Customer Case Studies From Vendors Appendix B -- Building The HealthCare Information Factory
506			_aAvailable to OhioLINK libraries
520	8		_aIn conclusion as you come to the end of this book, the concept of a Data Warehouse and its primary goal of serving the enterprise version of truth, and being the single platform for all the source of information will continue to remain intact and valid for many years to come. As we have discussed across many chapters and in many case studies, the limitations that existed with the infrastructures to create, manage and deploy Data Warehouses have been largely eliminated with the availability of Big Data technologies and infrastructure platforms, making the goal of the single version of truth a feasible reality. Integrating and extending Big Data into the Data Warehouse, and creating a larger decision support platform will benefit businesses for years to come. This book has touched upon governance and information lifecycle management aspects of Big Data in the larger program, however you can reuse all the current program management techniques that you follow for the Data Warehouse for this program and even implement agile approaches to integrating and managing data in the Data Warehouse. Technologies will continue to evolve in this spectrum and there will be more additions of solutions, which can be integrated if you follow the modular integration approaches to building and managing the Data Warehouse. The Appendix sections contain many more case studies and a special section on Healthcare Information Factory based on Big Data approaches. These are more guiding posts to help you align your thoughts and goals to building and integrating Big Data in your Data Warehouse
650		0	_aData warehousing
650		0	_aBig data
710	2		_aOhio Library and Information Network
776	0	8	_iPrint version: _aKrishnan, Krish. _tData warehousing in the age of big data. _dAmsterdam : Morgan Kaufmann is an imprint of Elsevier, 2013 _z9780124058910 _w(DLC) 2013004151 _w(OCoLC)832288558
856	4	0	_zConnect to resource _uhttps://learning.oreilly.com/library/view/~/9780124058910/?ar
942			_2lcc _cBK
999			_c3444 _d3444