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Big data imperatives

This book focuses on resolving key questions related to Enterprise Big Data Warehouses, BI Implementations and Analytics.


Big data is not just a buzzword, in the right hands, big data—the massive amounts of information organizations collect today—can be a powerful asset on the Analytics Journey to High Performance .

The book focuses on resolving the key big data-related questions on everyone’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 business intelligence (BI) applications?

Big Data Imperatives: Enterprise Big Data Warehouse, BI Implementations and Analytics. This opens a new window.

Big Data Imperatives: Enterprise Big Data Warehouse, BI Implementations and Analytics, co-authored by Soumendra Mohanty, Accenture Global Information Management Services lead, takes a look at the real value of big data, which lies not in the overwhelming size of it but rather in its effective use.


About the Book
Big Data Imperatives describes the complementary nature of traditional data warehouses and big data analytics platforms, and how they interact. The book aims to bring the big data and analytics realms together with a focus on architectures that leverage the scale and power of big data and the ability to integrate and apply analytics principles to data that previously was not possible.

This book is written for IT professionals, data warehousing, BI professionals, data analysis professionals, architects, developers and business users. It can also be used as a handbook for practitioners, helping them with 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.

Key Findings
Key Takeaways

  • Big data architectures

  • Big data design patterns

  • Implementation best practices

  • Understanding the technology and implementation of big data platforms and how to leverage them for analytics

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