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 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 bookintends to hold the interest of those new to big data and analytics by giving them a deep insight into the realm of big data.
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 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 bookintends to hold the interest of those new to big data and analytics by giving them a deep insight into the realm of big data.
![Big Data Imperatives: Enterprise Big Data Warehouse, BI Implementations and Analytics](http://img.images-bn.com/static/redesign/srcs/images/grey-box.png?v11.10.4)
Big Data Imperatives: Enterprise Big Data Warehouse, BI Implementations and Analytics
320![Big Data Imperatives: Enterprise Big Data Warehouse, BI Implementations and Analytics](http://img.images-bn.com/static/redesign/srcs/images/grey-box.png?v11.10.4)
Big Data Imperatives: Enterprise Big Data Warehouse, BI Implementations and Analytics
320Paperback(1st ed.)
Product Details
ISBN-13: | 9781430248729 |
---|---|
Publisher: | Apress |
Publication date: | 06/27/2013 |
Edition description: | 1st ed. |
Pages: | 320 |
Product dimensions: | 6.00(w) x 8.90(h) x 0.60(d) |