Big Data Imperatives

Big Data ImperativesApress (July 2013)| ISBN: 1430248726 | PDF + EPUB | 320 pages | 14.1 MB
Big Data Imperatives

Big data is emerging from the realm of one-off projects to mainstream business adoption; however, the real value of big data is not in the overwhelming size of it, but more in its effective use.This book addresses the following big data characteristics:Very large, distributed aggregations of loosely structured data – often incomplete and inaccessiblePetabytes/Exabytes of dataMillions/billions of people providing/contributing to the context behind the dataFlat schema’s with few complex interrelationshipsInvolves time-stamped eventsMade up of incomplete dataIncludes connections between data elements that must be probabilistically inferredBig Data Imperatives explains ‘what big data can do’. It can batch process millions and billions of records both unstructured and structured much faster and cheaper. Big data analytics provide a platform to merge all analysis which enables data analysis to be more accurate, well-rounded, reliable and focused on a specific business capability.Big Data Imperatives describes the complementary nature of traditional data warehouses and big-data analytics platforms and how they feed each other. This book aims to bring the big data and analytics realms together with a greater focus on architectures that leverage the scale and power of big data and the ability to integrate and apply analytics principles to data which earlier was not accessible.This book can also be used as a handbook for practitioners; helping them on methodology,technical architecture, analytics techniques and best practices. At the same time, this book intends to hold the interest of those new to big data and analytics by giving them a deep insight into the realm of big data.What you’ll learnUnderstanding the technology, implementation of big data platforms and their usage for analyticsBig data architecturesBig data design patternsImplementation best practicesWho this book is forThis book is designed for IT professionals, data warehousing, business intelligence professionals, data analysis professionals, architects, developers and business users.Table of ContentsChapter 1. “Big Data” in the EnterpriseChapter 2. The New Information Management ParadigmChapter 3. Big Data Implications for IndustryChapter 4. Emerging Database LandscapeChapter 5. Application Architectures for Big Data and AnalyticsChapter 6. Data Modeling Approaches for Big Data and Analytics SolutionsChapter 7. Big Data Analytics MethodologyChapter 8. Extracting Value From Big data: In-Memory Solutions, Real Time Analytics, And Recommendation SystemsChapter 9. Data ScientistDownload Rapidgator.nethttp://rapidgator.net/file/1b9371e507431e1e1210f83cb9eaa640/Apress.Big.Data.Imperatives.Jul.2013.rar.htmlDownload Uploaded.nethttp://ul.to/tqihhfbkDownload Letitbit.nethttp://u20528441.fduck.eu/AF_TA/rel/index.cfm?RST=UNF&TAD=429583&dl=am/download/45769.4c14eba53ab41ca4d87ac815cf6e/Apress.Big.Data.Imperatives.Jul.2013.rar.html