Tamr
1. Category: Data Integration, Database, Enterprise Software, Machine Learning
2. Domain: Data unification, Data curation, Data integration,
3. Founders: Andy Palmer, Ihab Ilyas, Mike Stonebraker
4. Established: 2012
5. Number of Employees: 101 – 250
6. Operating Status: Active
7. Funding status: Not disclosed
8. Website: www.tamr.com
9. Country: Greater Boston Area, East Coast, New England
10. Latest in News: last updated in 2016
Tamr is a software platform uses machine learning supplemented by human expertise mainly focuses in data Unification Company to unify and prepare data across myriad silos to deliver previously unavailable business-changing insights.
Company as a team began building a commercial-grade solution designed to tackle the challenge of connecting and enriching diverse data at scale, quickly and cost effectively and followed with the success of initial research at MIT CSAIL.
It deployed in production at a variety organizations, including information services providers, pharmaceutical firms and retailers. Tamr is responsible for helping customers their Industry 4.0 initiatives.
The software firstly analyze data sources by applying advanced algorithms and machine learning to connect and curate attributes and records and Uses machine learning to solve the data curation problem and makes data source connectivity and enrichment fast, cost-effective, scalable and accessible to the entire enterprise.
Tamr enhances in to three core capabilities: Catalog, Connect, and Consume. It provides services Catalog Internal & External Data Sources, Match & Classify Records from Thousands of Data Sets, Unify Attributes across all of Your Sources, Clean and Prepare Data for Analysis.
Tamr helps in making better business decisions by cleaning and mastering your data, effectively manage suppliers, spend and materials and quickly act upon latent data by combining Machine Learning and human expertise.
Tamr’s approach streamlines data integration with powerful Spark transformations and machine learning to ensure data in lakes is findable, accessible, interoperable, and reusable and quickly consolidates relevant data attributes for key entities such as customers, suppliers, assets and products.
Data lake management tools necessary for building out best-in-breed data operation pipelines to ensure that new data sources and records being added continue to be consolidated and unified over time with little effort.
Tamr consolidate manage and maintain custom data schema models that can be mapped against datasets throughout the data lake, data mappings are maintained and replicable across datasets with little manual effort. It uses human-guided machine learning to de-duplicate and cleanse the data.
Tamr has the ability to track records moving in and out of the data curation process using persistent ids which provide clear auditability of the data pipeline and provides a machine learning approach to help build best-in-breed data operation pipelines to streamline and automate the data curation process.
