Deep dives into data architecture, ML pipelines, dbt patterns, and the future of the modern data stack.
Data-driven solutions are becoming increasingly essential for businesses and organisations to remain competitive. By leveraging the power of data, companies can make informed decisions, drive growth, and optimise operations.
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Explore time-series forecasting algorithms โ ARIMA, Prophet, and LSTM โ and how to integrate them into production data pipelines for business planning.
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Raw data is all around us. The real value lies in its ability to provide actionable insights that drive informed decisions and improved business outcomes.
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A practical guide to setting up a production-grade Delta Lake on Databricks โ covering schema evolution, ACID transactions, and time travel queries.
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From modular SQL patterns to automated testing and CI/CD โ the dbt practices that separate hobby projects from enterprise-grade analytics engineering.
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How to design scalable ML feature pipelines on Apache Spark that can process billions of rows and serve fresh features to production ML models in near real-time.
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A hands-on tutorial on building a real-time data pipeline with Apache Kafka and Spark Structured Streaming โ from broker setup to Delta Lake ingestion.
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