Lake House using Azure Databricks

 
English Intermediate Analytics

The Lake House is an Open Data Management Architecture which unifies features of Data warehousing and Data Lake for advanced Analytics. The solution came up with lots of features under one roof to manage Batch and Real-Time processing data pipelines together or separately. The Delta Lake is an open-source project that allows building Lake House Architecture on the top of Data Lakes like HDFS, S3, ADLS, GCS using compute engines like Spark, Flink, PrestoDB, Trino through APIs of languages like Java, Python, Scala, SQL, Rust, Ruby and so on. In this session, we will use Azure Databrick's Delta Lake framework to build Stream and Batch pipeline together, create tables, register them for Databricks SQL and query them, create visuals and build dashboards.

Speaker

Chandrashekhar Deshpande

Microsoft Certified Azure Developer and Trainer

Mr.Chandrashekhar has 16+ years of experience in corporate training and 6+ years of experience in Architecting and Development of Real-life Projects. He is Microsoft Certified Trainer and conducts training on Azure. His expertise lies in training delivery across Big Data, Analytics, Machine Learning, and ML/AI services on Azure. His gamut of specialties is varied ranging from Apache Spark, Analytics and Machine Learning, Apache Kafka, Sqoop, Apache Flink, Apache Flume, Azure HDInsight, Hadoop, and its eco-system including Hive and HBase. Also, he has acquired requisite knowledge of Design Patterns (GoF and JEE), Java Performance Tuning, Java on Azure, Amazon Web Services, Liferay portal, Spring-Liferay integration, and JSE, JEE, Frameworks like Spring, Hibernate/JPA.

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