About This Course
Course Curriculum
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Introduction00:07:00
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Building a Data-driven Organization – Introduction00:04:00
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Data Engineering00:06:00
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Learning Environment & Course Material00:04:00
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Movielens Dataset00:03:00
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Introduction to Relational Databases00:09:00
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SQL00:05:00
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Movielens Relational Model00:15:00
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Movielens Relational Model: Normalization vs Denormalization00:16:00
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MySQL00:05:00
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Movielens in MySQL: Database import00:06:00
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OLTP in RDBMS: CRUD Applications00:17:00
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Indexes00:16:00
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Data Warehousing00:15:00
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Analytical Processing00:17:00
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Transaction Logs00:06:00
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Relational Databases – Wrap Up00:03:00
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Distributed Databases00:07:00
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CAP Theorem00:10:00
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BASE00:07:00
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Other Classifications00:07:00
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Introduction to KV Stores00:02:00
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Redis00:04:00
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Install Redis00:07:00
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Time Complexity of Algorithm00:05:00
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Data Structures in Redis : Key & String00:20:00
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Data Structures in Redis II : Hash & List00:18:00
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Data structures in Redis III : Set & Sorted Set00:21:00
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Data structures in Redis IV : Geo & HyperLogLog00:11:00
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Data structures in Redis V : Pubsub & Transaction00:08:00
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Modelling Movielens in Redis00:11:00
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Redis Example in Application00:29:00
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KV Stores: Wrap Up00:02:00
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Introduction to Document-Oriented Databases00:05:00
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MongoDB00:04:00
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MongoDB Installation00:02:00
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Movielens in MongoDB00:13:00
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Movielens in MongoDB: Normalization vs Denormalization00:11:00
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Movielens in MongoDB: Implementation00:10:00
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CRUD Operations in MongoDB00:13:00
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Indexes00:16:00
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MongoDB Aggregation Query – MapReduce function00:09:00
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MongoDB Aggregation Query – Aggregation Framework00:16:00
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Demo: MySQL vs MongoDB. Modeling with Spark00:02:00
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Document Stores: Wrap Up00:03:00
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Introduction to Search Engine Stores00:05:00
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Elasticsearch00:09:00
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Basic Terms Concepts and Description00:13:00
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Movielens in Elastisearch00:12:00
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CRUD in Elasticsearch00:15:00
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Search Queries in Elasticsearch00:23:00
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Aggregation Queries in Elasticsearch00:23:00
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The Elastic Stack (ELK)00:12:00
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Use case: UFO Sighting in ElasticSearch00:29:00
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Search Engines: Wrap Up00:04:00
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Introduction to Columnar databases00:06:00
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HBase00:07:00
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HBase Architecture00:09:00
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HBase Installation00:09:00
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Apache Zookeeper00:06:00
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Movielens Data in HBase00:17:00
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Performing CRUD in HBase00:24:00
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SQL on HBase – Apache Phoenix00:14:00
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SQL on HBase – Apache Phoenix – Movielens00:10:00
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Demo : GeoLife GPS Trajectories00:02:00
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Wide Column Store: Wrap Up00:04:00
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Introduction to Time Series00:09:00
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InfluxDB00:03:00
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InfluxDB Installation00:07:00
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InfluxDB Data Model00:07:00
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Data manipulation in InfluxDB00:17:00
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TICK Stack I00:12:00
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TICK Stack II00:23:00
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Time Series Databases: Wrap Up00:04:00
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Introduction to Graph Databases00:05:00
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Modelling in Graph00:14:00
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Modelling Movielens as a Graph00:10:00
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Neo4J00:04:00
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Neo4J installation00:08:00
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Cypher00:12:00
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Cypher II00:19:00
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Movielens in Neo4J: Data Import00:17:00
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Movielens in Neo4J: Spring Application00:12:00
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Data Analysis in Graph Databases00:05:00
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Examples of Graph Algorithms in Neo4J00:18:00
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Graph Databases: Wrap Up00:07:00
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Introduction to Big Data With Apache Hadoop00:06:00
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Big Data Storage in Hadoop (HDFS)00:16:00
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Big Data Processing : YARN00:11:00
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Installation00:13:00
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Data Processing in Hadoop (MapReduce)00:14:00
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Examples in MapReduce00:25:00
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Data Processing in Hadoop (Pig)00:12:00
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Examples in Pig00:21:00
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Data Processing in Hadoop (Spark)00:23:00
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Examples in Spark00:23:00
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Data Analytics with Apache Spark00:09:00
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Data Compression00:06:00
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Data serialization and storage formats00:20:00
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Hadoop: Wrap Up00:07:00
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Introduction Big Data SQL Engines00:03:00
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Apache Hive00:10:00
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Apache Hive : Demonstration00:20:00
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MPP SQL-on-Hadoop: Introduction00:03:00
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Impala00:06:00
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Impala : Demonstration00:18:00
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PrestoDB00:13:00
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PrestoDB : Demonstration00:14:00
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SQL-on-Hadoop: Wrap Up00:02:00
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Data Architectures00:05:00
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Introduction to Distributed Commit Logs00:07:00
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Apache Kafka00:03:00
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Confluent Platform Installation00:10:00
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Data Modeling in Kafka I00:13:00
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Data Modeling in Kafka II00:15:00
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Data Generation for Testing00:09:00
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Use case: Toll fee Collection00:04:00
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Stream processing00:11:00
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Stream Processing II with Stream + Connect APIs00:19:00
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Example: Kafka Streams00:15:00
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KSQL : Streaming Processing in SQL00:04:00
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KSQL: Example00:14:00
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Demonstration: NYC Taxi and Fares00:01:00
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Streaming: Wrap Up00:02:00
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Database Polyglot00:04:00
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Extending your knowledge00:08:00
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Data Visualization00:11:00
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Building a Data-driven Organization – Conclusion00:07:00
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Conclusion00:03:00