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The Modern Data Stack Explained: What The Future Holds

Alation

As data science is growing in popularity and importance , if your organization uses data science, you’ll need to pay more attention to picking the right tools for this. An example of a data science tool is Dataiku. Business Intelligence Tools: Business intelligence (BI) tools are used to visualize your data.

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How to build reusable data cleaning pipelines with scikit-learn

Snorkel AI

As the algorithms we use have gotten more robust and we have increased our compute power through new technologies, we haven’t made nearly as much progress on the data part of our jobs. Because of this, I’m always looking for ways to automate and improve our data pipelines. So why should we use data pipelines?

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How to build reusable data cleaning pipelines with scikit-learn

Snorkel AI

As the algorithms we use have gotten more robust and we have increased our compute power through new technologies, we haven’t made nearly as much progress on the data part of our jobs. Because of this, I’m always looking for ways to automate and improve our data pipelines. So why should we use data pipelines?

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3 Takeaways from Gartner’s 2018 Data and Analytics Summit

DataRobot Blog

These modern tools will auto-profile the data, detect joins and overlaps, and offer recommendations. With AI infused throughout, the industry is moving towards a place where data analytics is far less biased, and where citizen data scientists will have greater power and agility to accomplish more in less time.