商品簡介
Big Data Imperatives, focuses on resolving the key questions on every one's mind: Which data matters? Do you have enough data volume to justify the usage? How you want to process this amount of data? How long do you really need to keep it active for your analysis, marketing, and BI applications? 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. Your goal may be to obtain insight from voluminous data, with billions of loosely-structured bytes of data coming from different channels spread across different locations, which needs to be processed until the needle in the haystack is found. This book addresses the following big data characteristics: Very large, distributed aggregations of loosely structured data ? often incomplete and inaccessible Petabytes/Exabytes of data Millions/billions of people providing/contributing to the context behind the data Flat schema's with few complex interrelationships Involves time-stamped events Made up of incomplete data Includes connections between data elements that must be probabilistically inferred Big 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 learn Understanding the technology, implementation of big data platforms and their usage for analytics Big data architectures Big data design patterns Implementation best practices Who this book is for
This book is designed for IT professionals, data warehousing, business intelligence professionals, data analysis professionals, architects, developers and business users.
作者簡介
Soumendra Mohanty? is a Partner and leads Accenture?s Global Information Management Services practice. He is an expert within the Information Management area, focusing primarily on BI architectures, data warehouse, CRM/Customer Insight, MDM, Analytics and PCM solutions.? He is experienced in leading project teams through the lifecycle of a project, and has successfully helped sell and delivered BI and DW projects in multiple industries, including products, CPG, brokerage, banking, telecommunications, and retail.Soumendra has authored several books on data warehousing and Analytics and published numerous journals in DM Review. He has also presented in numerous international forums. His functional expertise ranges from Big Data Analytics, BI Architectures, Data Warehouse, CRM/Customer Insight, Supply Chain Analytics, Marketing Insights, & MDM.
