Realizing the potential of clean mastered data for businesses

Ihab Ilyas

Ringing in the New Data Year: What to Expect in 2019

2018 is quickly winding down. At Tamr, we’ve been asking ourselves: “What’s coming in 2019?” “Will it be the year of machine learning?” “What changes will we see?” Here are a few important trends to watch for the coming year.…

Dec 27, 2018 Featured Content

How to Clean Noisy and Erroneous Big Data Using Machine Learning

Data unification/deduplication and repair are proving to be difficult for many organizations. In fact, data unification and cleaning account for about 60% to 70% of the work of data scientists. It’s the most time-consuming, least rewarding data science task. Organizations…

Dec 4, 2018 Featured Content

Three Enablers For Machine Learning In Data Unification: Trust, Legacy, And Scale

Note: This article was originally posted on the O’Reilly website. Data unification is the process of combining multiple, diverse data sets and preparing them for analysis by matching, deduplicating, and otherwise cleaning the records (Figure 1). This effort consumes more…

Aug 30, 2017 Insights

From Data Variety to Data Opportunity

Among its well-known challenges, we are getting better and better at handling the volume aspect of Big Data; we buy more machines, we “shard” tables, and we even port solutions to clusters and MapReduce platforms.  But it is the “Variety”…

Jul 9, 2014 Insights