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In this hadoop project, learn about the features in Hive that allow us to perform analytical queries over large datasets.
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Hive Project- Understand the various types of SCDs and implement these slowly changing dimesnsion in Hadoop Hive and Spark.
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In this spark project, you will use the real-world production logs from NASA Kennedy Space Center WWW server in Florida to perform scalable log analytics with Apache Spark, Python, and Kafka.
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FEAST Feature Store Example- Learn to use FEAST Feature Store to manage, store, and discover features for customer churn prediction machine learning project.
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To understand cltv and the factors affecting cltv and to analyze various customer segments such as loyal, retained and churned.
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In this data science project, you will learn how to perform market basket analysis with the application of Apriori and FP growth algorithms based on the concept of association rule learning.
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