Tamr and the Data Lake

Tamr and the Data Lake

Tamr Unifies Datasets In Hadoop To Unlock Hidden Insights

Companies Struggle With Integrating Data In Hadoop
Hadoop has helped organizations significantly reduce the cost of data processing by spreading work over clusters built on commodity hardware as well as giving companies the ability to host massive amounts
of heterogeneous and diverse data sets. With the growing popularity of Hadoop, a significant amount of organizations have been creating Data Lakes, where they store data derived from structured and unstructured data sources in its raw format. However, these companies struggle with connecting and transforming the data into a unified dataset for business analysis without significant investment in time and money. This is largely because schema proflieration is rampant and very rarely are any two datasets structured exactly alike.

Tamr’s Matching Engine Unifies Data Within Hadoop
Tamr solves the biggest challenge in unifying datasets in Hadoop, namely connecting and cleaning the data so that it’s ready for analytics. Tamr is a data unification platform that leverages machine learning and customer expertise to create integrated, clean datasets with unrivaled speed and scalability. In particular, Tamr focuses on profiling datasets, creating ideal target schemas, and deduplicating records in order to prepare datasets for analysis.

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