Big Data Engineering In Depth
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What you'll learn
This course includes
- 19.3 hours of video
- Certificate of completion
- Access on mobile and TV
Course content
1 modules • 92 lessons • 19.3 hours of video
Big Data Engineering In Depth
92 lessons
• 19.3 hours
Big Data Engineering In Depth
92 lessons
• 19.3 hours
- Big Data Engineering In Depth Promo 00:09
- Ch.01-01 Course Introduction 10:58
- Ch.01-02 Getting the max benefit from this course 07:55
- Ch.01-03 Assignments, Labs, and Textbooks 06:02
- Ch.01-04 Course Content Overview 07:00
- Ch.02-01 Introduction To Data Management 11:51
- Ch.02-02 Data Abstraction 12:32
- Ch.02-03 Physical Layer 05:46
- Ch.02-04 Logical Layer 05:10
- Ch.02-05 View Layer 05:30
- Ch.02-06 Data Solution Thinking 07:03
- Ch.02-07 Introduction to DWH 10:14
- Ch.02-08 DWH Vs Transactional DB 09:57
- Ch.02-09 DWH BusinessTypes 08:31
- Ch.02-10 Use Cases For DWH Types and Transactional DB 10:21
- Ch.02-11 Multi Temperature Storage System 18:43
- Ch.02-12 DWH Characteristics and Architecture Components | DWH Architecture 10:49
- Ch.02-13 Source Systems Integration Process | DWH Architecture 11:08
- Ch.02-14 Source Systems Extraction Layer | DWH Architecture 09:12
- Ch.02-15 Staging Layer | DWH Architecture 05:04
- Ch.02-16 Data Modeling | DWH Architecture 29:46
- Ch.02-17 Dimension Types: Conformed Dimension | Data Modeling | DWH Architecture 06:20
- Ch.02-18 Dimension Types: Degenerate Dimension | Data Modeling | DWH Architecture 03:51
- Ch.02-19 Dimension Types: Junk Dimension | Data Modeling | DWH Architecture 10:03
- Ch.02-20 Dimension Types: Role Playing Dimension | Data Modeling | DWH Architecture 05:56
- Ch.02-21 Dimension Types: Outrigger Dimension | Data Modeling | DWH Architecture 03:12
- Ch.02-22 Dimension Types: Snowflake Dimension | Data Modeling | DWH Architecture 03:47
- Ch.02-23 Dimension Types: Slowly changing dimension SCD 0,1,2,3,4 | Data Modeling | DWH Architecture 13:17
- Ch.02-24 Dimension Types: Fast Changing Dimensions | Data Modeling | DWH Architecture 08:24
- Ch.02-25 Dimension Types: Shrunken Dimension | Data Modeling | DWH Architecture 05:57
- Ch.02-26 Dimension Types: Multi Valued Dimension | Data Modeling | DWH Architecture 10:49
- Ch.02-28 Dimension Types: Heterogeneous Dimension | Data Modeling | DWH Architecture 07:00
- Ch.02-27 Dimension Types: Swappable Dimension | Data Modeling | DWH Architecture 14:30
- Ch.02-29 Fact Tables | Data Modeling | DWH Architecture 33:31
- Ch.02-30 Schema Types | Data Modeling | DWH Architecture 15:33
- Ch.02-31 Introduction | ETL | DWH Architecture 17:08
- Ch.02-32 Best Practices | ETL | DWH Architecture 33:51
- Ch.02-33 Surrogate Vs Natural Key | Data Modeling 15:39
- Ch.02-34 Partitioning vs Bucketing | Data Modeling 12:24
- Ch.02-35 Kimball vs Inmon | Data Modeling 22:29
- Ch.03-01 Introduction To Distributed Systems | Hadoop 25:05
- Ch.03-02 Introduction To Distributed Systems | Hadoop 15:40
- Ch.03-03 Introduction To Hadoop 32:11
- Ch.03-04 HDFS | Hadoop 15:41
- Ch.03-05 YARN | Hadoop 39:41
- Ch.03-06 - Map Reduce | Hadoop 37:39
- Ch.03-07 - Combiner | Map Reduce | Hadoop 11:01
- Ch.03-08 - With vs Without Combiners | Map Reduce | Hadoop 15:50
- Ch.03-09 - Inverted Index | Map Reduce | Hadoop 21:04
- Ch.03-10 - Custom Writable Implementation | Map Reduce | Hadoop 18:04
- Ch.03-11 - Custom Partitioner | Map Reduce | Hadoop 17:37
- Ch.03-12 - Secondary Sort - Part 1 | Map Reduce | Hadoop 19:00
- Ch.03-13 - Secondary Sort - Part 2 | Map Reduce | Hadoop 13:32
- Ch.03-14 - Reduce Side Join | Map Reduce | Hadoop 23:57
- Ch.03-15 -Map Side Join | Map Reduce | Hadoop 09:58
- Ch.03-16 - Hadoop Filesystems and CLI | Hadoop 21:08
- Ch.03-17 - Anatomy of a File Read and Write | HDFS | Hadoop 20:21
- Ch.03-18 - Introduction to Apache Hive | Hive | Hadoop 13:02
- Ch.03-19- Apache Hive vs Traditional RDBMS | Hive | Hadoop 13:17
- Ch.03-20- Apache Hive Architecture | Hive | Hadoop 19:55
- Ch.03-21- Query Execution Flow | Hive | Hadoop 05:55
- Ch.03-22- Table Format | Hive | Hadoop 10:58
- Ch.03-23- Hive Database | Hive | Hadoop 09:44
- Ch.03-24- Hive Tables | Hive | Hadoop 37:58
- Ch.03-25- Hive Demo | Hive | Hadoop 17:29
- Ch.04-01: Introduction to Apache Spark 06:16
- Ch.04-02: Python Vs. Scala 10:46
- Ch.04-03: Introduction to Apache Spark 10:21
- Ch.04-04: About Databricks 08:02
- Ch.04-05: Spark In The Data Platforms 06:27
- Ch.04-06: Running Spark 02:30
- Ch.04-07: Demo: Running Spark on Linux Ubuntu 05:05
- Ch.04-08: Demo: Running Spark on MacOS 03:36
- Ch.04-09: Demo: Running Spark on Windows 09:08
- Ch.04-10: Demo: Running Spark on Databricks 05:19
- Ch.04-11: From Map Reduce To Spark 06:08
- Ch.04-12: Spark Characteristics 10:28
- Ch.04-13: Spark Applications 03:03
- Ch.04-14: Spark Driver 08:09
- Ch.04-15: Spark Session 07:45
- Ch.04-16: Spark Cluster Manager 05:22
- Ch.04-17: Spark Execution Mode 08:09
- Ch.04-18: Spark Executors 03:04
- Ch.04-19: Spark Data Partitioning 06:31
- Ch.04-20: Spark Operations 17:41
- Ch.04-21: Transformations Narrow Vs Wide 06:57
- Ch.04-22: Demo: Immutability In Spark 06:44
- Ch.04-23: Demo: RDD Text Manipulation 03:48
- Ch.04-24: Demo: GroupByKey Vs. ReduceByKey 06:57
- Ch.04-25: Demo: Joining RDDs 19:17
- Ch.04-26: Demo: Spark RDD APIs 21:15
- Ch.04-27: Demo: Repartition Vs. Coalesce 17:05
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