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The Modern Data Stack Explained: What The Future Holds

Alation

You should look for a data warehouse that is scalable, flexible, and efficient. Popular cloud data warehouses today include Snowflake, Databricks, and BigQuery. If your organization is large, you definitely need to look for robustness. Good data warehouses should be reliable. An example of a data science tool is Dataiku.

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How to build reusable data cleaning pipelines with scikit-learn

Snorkel AI

Python’s definitely the most popular. Or do you still think it takes a lot of data science knowledge, so we’re a while away from having SMEs drive this process? And we’ve been talking about citizen data scientists for the longest time. AB : Makes sense. JG : No, I don’t know.

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How to build reusable data cleaning pipelines with scikit-learn

Snorkel AI

Python’s definitely the most popular. Or do you still think it takes a lot of data science knowledge, so we’re a while away from having SMEs drive this process? And we’ve been talking about citizen data scientists for the longest time. AB : Makes sense. JG : No, I don’t know.

article thumbnail

How to build reusable data cleaning pipelines with scikit-learn

Snorkel AI

Python’s definitely the most popular. Or do you still think it takes a lot of data science knowledge, so we’re a while away from having SMEs drive this process? And we’ve been talking about citizen data scientists for the longest time. AB : Makes sense. JG : No, I don’t know.

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Data science

Dataconomy

Data science is an interdisciplinary field that utilizes advanced analytics techniques to extract meaningful insights from vast amounts of data. This helps facilitate data-driven decision-making for businesses, enabling them to operate more efficiently and identify new opportunities.