The enterprise data warehouse (EDW) community has entered a new realm of meeting new and growing business requirements in the era of big data. Common challenges include:
These pressing needs raise more than a few urgent questions, such as:
This white paper provides detailed guidance for designing and administering the necessary deployment processes to meet these requirements. Ralph Kimball fills the hole where there is a lack of specific guidance in the industry as to how the EDW needs to respond to the big data analytics challenge, and what design elements are needed to support these new requirements.
- extreme integration
- semi- and un-structured data sources
- petabytes of behavioral and image data accessed through MapReduce/Hadoop
- massively parallel relational database
- structural considerations for the EDW to support predictive and other advanced analytics.
These pressing needs raise more than a few urgent questions, such as:
- How do you handle the explosion and diversity of data sources from conventional and non-conventional sources?
- What new and existing technologies are needed to deepen the understanding of business through big data analytics?
- What technological requirements are needed to deploy big data projects?
- What potential organizational and cultural impacts should be considered?
This white paper provides detailed guidance for designing and administering the necessary deployment processes to meet these requirements. Ralph Kimball fills the hole where there is a lack of specific guidance in the industry as to how the EDW needs to respond to the big data analytics challenge, and what design elements are needed to support these new requirements.
0 comments:
Post a Comment