Archive

Using Tamr’s metadata enrichment, discovery, and standardization to unlock new possibilities in data management

At the genesis of any data-driven initiative or project, we must first find and access the relevant data in our organization to pull together. Better yet if the data we find can be inter-operable or re-usable across both new and…

Feb 11, 2020 Featured Content

Five Signs That You Might Have a Know-Your-Customer Problem

Is it taking too long to onboard new customers due to risk, compliance and due- diligence screening? Are your sales reps not getting proper commissions for their sales? Are you missing important KPIs in customer service? Are you not getting…

Nov 20, 2019 Featured Content

Building a Future for Life Sciences Data

After a successful early career in R&D in Silicon Valley, I spent 12 years working as a carpenter. This may sound like a big U-turn. But, while I loved the intellectual piece of science, I really loved the people aspect…

Nov 7, 2019 Featured Content

Why Low Latency Matching is critical to Data Mastering at Scale

It’s common to think of data mastering as the way we turn our disparate and dirty data sources into something clean that we can use to power data applications. A few dozen sources of customer data go through the mastering…

Oct 18, 2019 Featured Content

Better Feedback for Better Data Quality

By Margaret Soderholm   Here’s a basic scenario: You’re a marketing analyst looking for some numbers to gauge how well a recent promotion did. In checking the May sales reports, you find the numbers you need, but something seems off.…

Jul 8, 2015 Featured Content

Embracing the Data Variety Challenge: The Time Has Come.

Three years ago, my partner Mike Stonebraker was working on a research project at MIT to test the boundaries of data integration and curation. Mike and his fellow researchers wanted to see if it was possible to connect thousands or…

May 18, 2014 Insights

Three Generations of Data Integration Systems

(In this entry, I explain the three generations of data integration products and note what appears to have caused the transitions between the product families.) In the 1990s, data warehouses arrived on the scene. Led by the major retailers, customer-facing…

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