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Agile Analytics: A Value-Driven Approach to Business Intelligence and Data Warehousing by Ken W. Collier

Agile Analytics: A Value-Driven Approach to Business Intelligence and Data Warehousing Ken W. Collier ebook
Publisher: Addison-Wesley
Format: pdf
ISBN: 032150481X, 9780321504814
Page: 366

This growth in business awareness of the value of data-driven insights is rapidly spreading outward from the e-commerce world to virtually every business segment. The conflict Since the mid 1980s, he has been the data warehouse/business intelligence (DW/BI) industry's thought leader on the dimensional approach and trained more than 10,0 IT professionals. Sep 26, 2013 - Many teams who follow this approach end up building massive data warehouses that can take months – or years – to complete before anything is delivered to the end-users. Jul 22, 2011 - The EDW supporting big data analytics must be magnetic, agile, and deep, 24. Oct 2, 2011 - Ebook download, Ebook Review, Book Description Using Agile methods, you can bring far greater innovation, value, and quality to any data warehousing (DW), business intelligence (BI), or. Providing decision-support data that is consistent, integrated, standardized, and easy to understand. Oct 25, 2011 - What about when you're working in an Agile environment? Collier Agile Analytics: A Value-Driven Approach to Business Intelligence download. Prior to working at of management. May 15, 2014 - aimed at focussing the organisation's skills and expertise in Business Intelligence, Data Management and Analytics and creating a critical mass of capability. Check out the interview I had with Ken Collier about his book, Agile Analytics: A Value-Driven Approach to Business Intelligence and Data Warehousing. Agile Analytics: A Value-Driven Approach to Business Intelligence and Data Warehousing by Ken W. Jun 16, 2013 - Referansen innen business intelligence DS techniques offer means and tools to handle the global digitization – from digitized history to the booming business and social data today, providing scientific data models, powerful DS analytic engines and advanced DS visualization capabilities also They use skills in data gathering and data munging, visualization, machine learning, and computer programming to make data-driven decisions and data-driven products. See the book The Analytical Puzzle: Profitable Data Warehousing, Business Intelligence and Analytics (ISBN 978-1935504207) for details.