Unlocking SQL with Kotlin Data Analytics: A Practical Exploration

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Unlocking SQL with Kotlin Data Analytics: A Practical Exploration Aleksei Zinovev @zaleslaw

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Bio ● Project Lead, Kotlin for Data Science ● Distributed ML enthusiast ● Apache Ignite PMC ● TensorFlow Contributor ● Happy father and husband ● https://github.com/zaleslaw ● https://twitter.com/zaleslaw

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Motivation Kotlin Community Python, Pandas, Matplotlib Kotlin Dev who just need to visualize some data from CSV

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DataFrame as a Data Structure

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File Data Exploration

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DataFrame as a Hierarchical Data Structure

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Okay, wait, what about databases?

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Okay, wait, what about databases?

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Okay, wait, what about databases?

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Okay, wait, what about databases?

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Main issues for Backend Kotlin Devs ● Fragmented Reporting Tools ● Context Switching Between IDE and Database Tools ● Inconsistent SQL Dialects and JDBC Implementations ● Difficulty in Integrating Multiple Data Sources (Files and Databases) ● Export and Usability Challenges ● Limited Presentation and Sharing Among Kotlin Developers

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Our Solution for Backend Kotlin Devs ● Utilize Kotlin Notebooks in IntelliJ IDEA for all data analysis tasks. ● Conduct database tasks directly in Kotlin Notebooks, avoiding frequent switching between tools. ● Standardize database access API across different systems using the Kotlin DataFrame library. ● Simplify data integration by merging data from various sources with the Kotlin DataFrame library. ● Easily share and present results via export options for reports and charts.

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SQL database analysis

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Data Source in Demo: IMDB SQL Database

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KDA useful links (replace with QR code) 1. Kotlin DataFrame documentation 2. Kotlin DataFrame examples 3. Kandy documentation 4. Kandy Quick Start Guide 5. Kandy examples

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Thank you, and don’t forget to vote @zaleslaw