Tamr

Tamr’s data unification platform catalogues, connects and curates hundreds or thousands of internal and external data sources through a combination of machine learning algorithms and human expert guidance reducing the cost, time and effort of preparing data for analysis. Tamr, catalogs, connects and curates the vast reserves of underutilized internal and external data using a combination of machine learning with human guidance so enterprises can use all their data for analytics.

Tamr dynamically catalogs the organization’s information assets with their crawlers, entity tagging, and metadata visualization features to provide a comprehensive, organized, bottom-up inventory of all information assets within enterprise.

Data sources include JDBC data sources, Standard file systems, Content management systems (CMS), such as Sharepoint, Documentum, Alfresco, and Big Data stores, such as HDFS / Hive, Amazon S3 / RedShift and Google Cloud Storage / BigQuery. RESTful APIs and a variety of export formats makes it easy to tie Tamr into existing infrastructure, allowing data scientists and business analysts to use familiar software, such as QlikTech, Tableau, SAS, IBM Cognos, Recorded Future, Statwing and Zoomdata.

Tamr

Using multi-stage machine learning techniques that span statistical analysis, classification, and cluster analysis, Tamr automatically develops and continuously maintains models of data source semantics and entity resolution, both within and across sources.