数据挖掘实验室
Custom-built search engine and metadata repository. The first option is about creating an integrated, centralized metadata repository and building a powerful search engine from scratch. It provides industries specific custom features and greater flexibility; however, it is a complex and time-consuming task. Any slippages in timelines will directly impact development cost.
数据挖掘实验室
Custom-built search engine over vendor metadata solution. The second option is to build a custom search engine over the enterprise metadata repository that is implemented using metadata vendor tool e.g., ASG Rochade or Informatica Metadata Manager (SuperGlue). The advantage of this option is that metadata integration at the enterprise level can be expedited using vendor tool. It is scalable and can easily accommodate other BI metadata like extract, transform and load metadata for example. However, interoperability of a custom built search engine with a metadata vendor tool may remain a challenge. 数据挖掘研究院
数据挖掘交友
Vendor search engine on top of custom metadata repository. The third option is similar to the first one in the sense that an integrated, centralized custom metadata repository is built, but it is different in the sense that an enterprise search vendor like Autonomy, Endeca or FAST search engine is deployed on top of it. On the positive side of this option, development time is reduced dramatically, the customized set of BI report metadata is captured and the metadata repository can be easily integrated with the vendor search engine to index BI report metadata. On the negative side, maintaining security across BI applications could be a challenge.
