Insights

Blogs, tutorials and case studies from our product experts and industry thought leaders to learn how to get the most out of your data.

How to Solve the Biggest Challenges in Enterprise AI

Leveraging a holistic data strategy helps your organization avoid the common pitfalls of AI adoption in the enterprise. Success depends on six pillars...

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MaRS & ThinkData Apply Machine Learning to Ontario Businesses

The MaRS team is using ThinkData’s technology to link records across multiple sources to understand Canadian start-up and scale-up activity.

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(Re): Softbear Developer at ThinkData Works

ThinkData Works provides the best data – through our platform and to our new employees. Take a look at our offer letter to see just a few of the perks.

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The Data Behind Love #ValentinesDay

A data analysis on how business are tapping into social media data in order to fuel their holiday marketing initiatives to increase sales.

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ThinkData on Entity Resolution at TMLS 2019

See Data Scientists Hoyoung Jang and Cheng Lin speak on scaleable entity resolution at TMLS 2019.

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The Difference Between Data Cleansing and Data Enrichment

There are plenty of steps between raw data and data that's ready for modeling & analysis – here's difference between data cleansing and data enrichment.

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#Womenintech is more than just a hashtag

Creating equal opportunities for women in tech must start early and continue throughout their careers to ensure diversity and equality in the workforce.

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Refined Data is the Key to Train Machine Learning

Refined, standardized data is the key to train machine learning in order to achieve meaningful results.

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Namara Ingest vs. a Standard ETL

Understand why we built our Ingest pipeline the way we did, and why generic ETL solutions fall short when it comes to handling data variety.

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Beyond the Startup Work Perks: Life at ThinkData

What's it like working at a startup like ThinkData? We ride that line between delivering enterprise solutions and keeping the spirit of fun and creativity.

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Adapt or Die: why your business strategy is failing your data strategy

Data projects are failing, but the problem isn't your data team – find out why business goals and data outcomes aren't lining up and what to do about it.

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Bridging the Digital Divide

Open data cannot live up to its potential until available data becomes accessible information – explore the historical gap and the progress being made.

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