Topics Covered in this Chapter
- This chapter covers big data and their potential in analytics space, mainly to enable readers to gain new insights that were previously hidden, and to use information that was not previously leveraged from big data and analytics.
- It provides a detailed solution blueprint for designing and developing big data analytical services that can be reused across the enterprise by using common design components and standards.
- How big data and analytics area users can leverage data services to access data needed for advanced analytics and make decisions in real time is also explained.
- There are several case studies presented from organizations that have successfully implemented big data and mobile-based analytics services, leveraging the Data as a Service (DaaS) framework.
“Without big data analytics, companies are blind and deaf, wandering out onto the Web like deer on a freeway.”
—Geoffrey Moore, Technology Visionary and Author
As many of us have witnessed, the rapid explosion of data in all its forms has turned into a deluge of remarkable proportions. A major portion of the data generated over recent decades has been from the world of unstructured data—everything from social media posts, mobile phone texts, and tweets to credit card transactions and sensor-generated data. In addition to this, the advent of Cloud computing has introduced the delivery of computer services via the Internet, with a large amount ...