- Practical Big Data Analytics
- Nataraj Dasgupta
- 145字
- 2021-07-02 19:26:19
Big Data Mining for the Masses
Implementing a big data mining platform in an enterprise environment that serves specific business requirements is non-trivial. While it is relatively simple to build a big data platform, the novel nature of the tools present a challenge in terms of adoption by business-facing users used to traditional methods of data mining. This, ultimately, is a measure of how successful the platform becomes within an organization.
This chapter introduces some of the salient characteristics of big data analytics relevant for both practitioners and end users of analytics tools. This will include the following topics:
- What is big data mining?
- Big data mining in the enterprise:
- Building a use case
- Stakeholders of the solution
- Implementation life cycle
- Key technologies in big data mining:
- Selecting the hardware stack:
- Single/multinode architecture
- Cloud-based environments
- Selecting the software stack:
- Hadoop, Spark, and NoSQL
- Cloud-based environments
- Selecting the hardware stack:
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