Section 1 : Introduction
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Lecture 1 | Introduction | |
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Lecture 2 | Building a Data-driven Organization - Introduction | 00:03:49 Duration |
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Lecture 3 | Data Engineering | 00:06:10 Duration |
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Lecture 4 | Learning Environment & Course Material | |
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Lecture 5 | Movielens Dataset | 00:03:18 Duration |
Section 2 : Relational Database Systems
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Lecture 1 | Introduction to Relational Databases | 00:08:36 Duration |
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Lecture 2 | SQL | 00:04:47 Duration |
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Lecture 3 | Movielens Relational Model | 00:14:52 Duration |
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Lecture 4 | Movielens Relational Model Normalization vs Denormalization | 00:15:33 Duration |
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Lecture 5 | MySQL | 00:05:06 Duration |
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Lecture 6 | Movielens in MySQL Database import | 00:05:42 Duration |
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Lecture 7 | OLTP in RDBMS CRUD Applications | 00:17:06 Duration |
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Lecture 8 | Indexes | 00:15:34 Duration |
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Lecture 9 | Data Warehousing | 00:15:27 Duration |
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Lecture 10 | Analytical Processing | 00:16:37 Duration |
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Lecture 11 | Transaction Logs | |
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Lecture 12 | Relational Databases - Wrap Up | 00:03:04 Duration |
Section 3 : Database Classification
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Lecture 1 | Distributed Databases | 00:07:25 Duration |
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Lecture 2 | CAP Theorem | 00:09:55 Duration |
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Lecture 3 | BASE | 00:07:18 Duration |
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Lecture 4 | Other Classification | 00:06:58 Duration |
Section 4 : Key-Value Store
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Lecture 1 | Introduction to KV Stores | 00:02:21 Duration |
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Lecture 2 | Redis | 00:03:57 Duration |
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Lecture 3 | Install Redis | 00:07:07 Duration |
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Lecture 4 | Time Complexity of Algorithm | 00:04:40 Duration |
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Lecture 5 | Data Structures in Redis Key & String | 00:20:17 Duration |
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Lecture 6 | Data Structures in Redis II Hash & List | 00:18:14 Duration |
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Lecture 7 | Data structures in Redis III Set & Sorted Set | 00:20:34 Duration |
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Lecture 8 | Data structures in Redis IV Geo & HyperLogLog | 00:10:33 Duration |
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Lecture 9 | Data structures in Redis V Pubsub & Transaction | 00:07:51 Duration |
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Lecture 10 | Modelling Movielens in Redis | 00:11:23 Duration |
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Lecture 11 | Redis Example in Application | 00:28:54 Duration |
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Lecture 12 | KV Stores Wrap Up | 00:02:03 Duration |
Section 5 : Document-Oriented Databases
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Lecture 1 | Introduction to Document-Oriented Databases | 00:04:33 Duration |
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Lecture 2 | MongoDB | 00:03:47 Duration |
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Lecture 3 | MongoDB installation | 00:01:30 Duration |
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Lecture 4 | Movielens in MongoDB | 00:13:12 Duration |
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Lecture 5 | Movielens in MongoDB Normalization vs Denormalization | 00:11:20 Duration |
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Lecture 6 | Movielens in MongoDB Implementation | 00:10:00 Duration |
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Lecture 7 | CRUD Operations in MongoDB | 00:12:46 Duration |
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Lecture 8 | Indexes | |
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Lecture 9 | MongoDB Aggregation Query - MapReduce function | 00:09:19 Duration |
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Lecture 10 | MongoDB Aggregation Query - Aggregation Framework | 00:15:39 Duration |
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Lecture 11 | Demo MySQL vs MongoDB | 00:01:49 Duration |
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Lecture 12 | Document Stores Wrap Up | 00:03:07 Duration |
Section 6 : Search Engine
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Lecture 1 | Introduction to Search Engine Stores | 00:05:12 Duration |
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Lecture 2 | Elasticsearch | 00:08:34 Duration |
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Lecture 3 | Basic Terms Concepts and Description | 00:12:48 Duration |
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Lecture 4 | Movielens in Elastisearch | 00:11:42 Duration |
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Lecture 5 | CRUD in Elasticsearch | 00:15:10 Duration |
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Lecture 6 | Search Queries in Elasticsearch | 00:22:52 Duration |
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Lecture 7 | Aggregation Queries in Elasticsearch | 00:14:08 Duration |
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Lecture 8 | The Elastic Stack (ELK) | 00:11:44 Duration |
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Lecture 9 | Use case UFO Sighting in ElasticSearch | 00:28:47 Duration |
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Lecture 10 | Search Engines Wrap Up | 00:03:48 Duration |
Section 7 : Wide Column Store
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Lecture 1 | Introduction to Columnar databases | 00:06:29 Duration |
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Lecture 2 | HBase | 00:06:53 Duration |
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Lecture 3 | HBase Architecture | 00:08:58 Duration |
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Lecture 4 | HBase Installation | 00:08:46 Duration |
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Lecture 5 | Apache Zookeeper | 00:06:28 Duration |
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Lecture 6 | Movielens Data in HBase | 00:18:06 Duration |
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Lecture 7 | Performing CRUD in HBase | 00:24:20 Duration |
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Lecture 8 | SQL on HBase - Apache Phoenix | 00:13:43 Duration |
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Lecture 9 | SQL on HBase - Apache Phoenix - Movielens | 00:10:08 Duration |
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Lecture 10 | Demo GeoLife GPS Trajectories | 00:01:46 Duration |
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Lecture 11 | Wide Column Store Wrap Up | 00:04:43 Duration |
Section 8 : Time Series Databases
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Lecture 1 | Introduction to Time Series | 00:09:26 Duration |
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Lecture 2 | InfluxDB | 00:02:50 Duration |
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Lecture 3 | InfluxDB Installation | 00:06:35 Duration |
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Lecture 4 | InfluxDB Data Model | 00:07:27 Duration |
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Lecture 5 | Data manipulation in InfluxDB | 00:16:37 Duration |
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Lecture 6 | TICK Stack I | 00:11:47 Duration |
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Lecture 7 | TICK Stack II | 00:22:57 Duration |
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Lecture 8 | Time Series Databases Wrap Up |
Section 9 : Graph Databases
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Lecture 1 | Introduction to Graph Databases | 00:05:00 Duration |
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Lecture 2 | Modelling in Graph | 00:13:38 Duration |
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Lecture 3 | Modelling Movielens as a Graph | 00:10:00 Duration |
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Lecture 4 | Neo4J | 00:03:32 Duration |
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Lecture 5 | Neo4J installation | 00:08:27 Duration |
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Lecture 6 | Cypher | 00:12:20 Duration |
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Lecture 7 | Cypher II | 00:19:09 Duration |
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Lecture 8 | Movielens in Neo4J Data Import | 00:17:16 Duration |
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Lecture 9 | Movielens in Neo4J Spring Application | 00:11:33 Duration |
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Lecture 10 | Data Analysis in Graph Databases | 00:05:10 Duration |
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Lecture 11 | Examples of Graph Algorithms in Neo4J | 00:18:20 Duration |
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Lecture 12 | Graph Databases Wrap Up | 00:06:56 Duration |
Section 10 : Hadoop Platform
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Lecture 1 | Introduction to Big Data With Apache Hadoop | 00:06:23 Duration |
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Lecture 2 | Big Data Storage in Hadoop (HDFS) | 00:15:47 Duration |
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Lecture 3 | Big Data Processing YARN | 00:11:01 Duration |
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Lecture 4 | Installation | 00:12:41 Duration |
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Lecture 5 | Data Processing in Hadoop (MapReduce) | 00:14:01 Duration |
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Lecture 6 | Examples in MapReduce | 00:24:51 Duration |
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Lecture 7 | Data Processing in Hadoop (Pig) | 00:11:45 Duration |
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Lecture 8 | Examples in Pig | 00:21:19 Duration |
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Lecture 9 | Data Processing in Hadoop (Spark) | 00:08:48 Duration |
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Lecture 10 | Examples in Spark | 00:22:37 Duration |
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Lecture 11 | Data Analytics with Apache Spark | 00:09:00 Duration |
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Lecture 12 | Data Compression | 00:05:41 Duration |
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Lecture 13 | Data serialization and storage formats | 00:19:50 Duration |
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Lecture 14 | Hadoop Wrap Up | 00:07:06 Duration |
Section 11 : Big Data SQL Engines
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Lecture 1 | Introduction Big Data SQL Engines | 00:02:51 Duration |
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Lecture 2 | Apache Hive | 00:10:25 Duration |
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Lecture 3 | Apache Hive Demonstration | 00:19:40 Duration |
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Lecture 4 | MPP SQL-on-Hadoop Introduction | 00:03:25 Duration |
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Lecture 5 | Impala | 00:05:35 Duration |
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Lecture 6 | Impala Demonstration | 00:17:55 Duration |
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Lecture 7 | PrestoDB | 00:13:12 Duration |
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Lecture 8 | PrestoDB Demonstration | 00:13:35 Duration |
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Lecture 9 | SQL-on-Hadoop Wrap Up | 00:01:58 Duration |
Section 12 : Distributed Commit Log
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Lecture 1 | Data Architectures | 00:04:45 Duration |
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Lecture 2 | Introduction to Distributed Commit Logs | 00:06:30 Duration |
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Lecture 3 | Apache Kafka | 00:02:55 Duration |
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Lecture 4 | Confluent Platform Installation | 00:10:07 Duration |
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Lecture 5 | Data Modeling in Kafka I | 00:12:48 Duration |
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Lecture 6 | Data Modeling in Kafka II | 00:14:59 Duration |
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Lecture 7 | Data Generation for Testing | 00:08:29 Duration |
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Lecture 8 | Use case Toll fee Collection | 00:04:23 Duration |
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Lecture 9 | Stream processing | 00:11:05 Duration |
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Lecture 10 | Stream Processing II with Stream + Connect APIs | 00:19:06 Duration |
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Lecture 11 | Example Kafka Streams | 00:15:02 Duration |
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Lecture 12 | KSQL Streaming Processing in SQL | 00:04:10 Duration |
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Lecture 13 | KSQL Example | 00:14:11 Duration |
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Lecture 14 | Demonstration NYC Taxi and Fares | 00:01:28 Duration |
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Lecture 15 | Streaming Wrap Up | 00:02:15 Duration |
Section 13 : Summary
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Lecture 1 | Database Polyglot | 00:03:44 Duration |
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Lecture 2 | Extending your knowledge | 00:08:29 Duration |
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Lecture 3 | Data Visualization | 00:10:49 Duration |
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Lecture 4 | Building a Data-driven Organization - Conclusion | 00:06:52 Duration |
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Lecture 5 | Conclusion | 00:03:09 Duration |