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Analyze Data Faster with an Open Source Columnar Database

MariaDB

If you are looking for the scalability and performance needed to support interactive, ad hoc analytics on billions of rows – and with SQL – this latest Data Science Central webinar will show you how to combine distributed, columnar storage and parallel query processing with powerful aggregate functions to deliver faster time to insight using modern, on-demand analytics, as well as how to leverage the power of Kafka and Spark connectors to plug into existing data pipelines. We will discuss the architectural overview of columnar databases, share real-world use cases and give a live demonstration.
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It’s hardly a surprise to anyone in the tech and related industries that “data scientist” is the best job to have these days. After all, this has been what sources like the Harvard Business Review and Glassdoor report for what is now four years in a row. And even if we take the base salary of $108,000 out of the equation, the position is still plenty attractive on all other dimensions. For example, the current shift towards using machine learning to fast-track business growth secures a steady cross-industry need for skilled professionals capable of handling data and the emerging technologies. The infographic below, produced by our friends over at 365DataScience, suggests that the field is evolving and, with it, the typical professional evolves as well.

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