Criticism of existing software implementations The main reasons cited are: Project costs: costs typically in the hundreds of thousands of dollars Time: lack of enough time to deal with large-scale data cleansing software Security: concerns over sharing information, giving an application access across systems, and effects on legacy systems Scalability: Due to the absence of unique identifiers in records, record linkage is computationally expensive and difficult to scale. Accuracy: Changing business data and capturing of all rules for linking is a tough and extensive exercise See also Capacity optimization Content-addressable storage Data deduplication Delta encoding Entity linking Entity-attribute-value model Identity resolution Linked data Named-entity recognition Open data Schema matching Single-instance storage Author Name Disambiguation Notes and references External links Data Linkage Project at Penn State, USA Stanford Entity Resolution Framework Dedoop - Deduplication with Hadoop Privacy Enhanced Interactive Record Linkage at Texas A&M University An Overview Of Data Matching Data management