Big Data Engineering In Depth
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17 learners
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 Promo00:09
- Ch.01-01 Course Introduction10:58
- Ch.01-02 Getting the max benefit from this course07:55
- Ch.01-03 Assignments, Labs, and Textbooks06:02
- Ch.01-04 Course Content Overview07:00
- Ch.02-01 Introduction To Data Management11:51
- Ch.02-02 Data Abstraction12:32
- Ch.02-03 Physical Layer05:46
- Ch.02-04 Logical Layer05:10
- Ch.02-05 View Layer05:30
- Ch.02-06 Data Solution Thinking07:03
- Ch.02-07 Introduction to DWH10:14
- Ch.02-08 DWH Vs Transactional DB09:57
- Ch.02-09 DWH BusinessTypes08:31
- Ch.02-10 Use Cases For DWH Types and Transactional DB10:21
- Ch.02-11 Multi Temperature Storage System18:43
- Ch.02-12 DWH Characteristics and Architecture Components | DWH Architecture10:49
- Ch.02-13 Source Systems Integration Process | DWH Architecture11:08
- Ch.02-14 Source Systems Extraction Layer | DWH Architecture09:12
- Ch.02-15 Staging Layer | DWH Architecture05:04
- Ch.02-16 Data Modeling | DWH Architecture29:46
- Ch.02-17 Dimension Types: Conformed Dimension | Data Modeling | DWH Architecture06:20
- Ch.02-18 Dimension Types: Degenerate Dimension | Data Modeling | DWH Architecture03:51
- Ch.02-19 Dimension Types: Junk Dimension | Data Modeling | DWH Architecture10:03
- Ch.02-20 Dimension Types: Role Playing Dimension | Data Modeling | DWH Architecture05:56
- Ch.02-21 Dimension Types: Outrigger Dimension | Data Modeling | DWH Architecture03:12
- Ch.02-22 Dimension Types: Snowflake Dimension | Data Modeling | DWH Architecture03:47
- Ch.02-23 Dimension Types: Slowly changing dimension SCD 0,1,2,3,4 | Data Modeling | DWH Architecture13:17
- Ch.02-24 Dimension Types: Fast Changing Dimensions | Data Modeling | DWH Architecture08:24
- Ch.02-25 Dimension Types: Shrunken Dimension | Data Modeling | DWH Architecture05:57
- Ch.02-26 Dimension Types: Multi Valued Dimension | Data Modeling | DWH Architecture10:49
- Ch.02-28 Dimension Types: Heterogeneous Dimension | Data Modeling | DWH Architecture07:00
- Ch.02-27 Dimension Types: Swappable Dimension | Data Modeling | DWH Architecture14:30
- Ch.02-29 Fact Tables | Data Modeling | DWH Architecture33:31
- Ch.02-30 Schema Types | Data Modeling | DWH Architecture15:33
- Ch.02-31 Introduction | ETL | DWH Architecture17:08
- Ch.02-32 Best Practices | ETL | DWH Architecture33:51
- Ch.02-33 Surrogate Vs Natural Key | Data Modeling15:39
- Ch.02-34 Partitioning vs Bucketing | Data Modeling12:24
- Ch.02-35 Kimball vs Inmon | Data Modeling22:29
- Ch.03-01 Introduction To Distributed Systems | Hadoop25:05
- Ch.03-02 Introduction To Distributed Systems | Hadoop15:40
- Ch.03-03 Introduction To Hadoop32:11
- Ch.03-04 HDFS | Hadoop15:41
- Ch.03-05 YARN | Hadoop39:41
- Ch.03-06 - Map Reduce | Hadoop37:39
- Ch.03-07 - Combiner | Map Reduce | Hadoop11:01
- Ch.03-08 - With vs Without Combiners | Map Reduce | Hadoop15:50
- Ch.03-09 - Inverted Index | Map Reduce | Hadoop21:04
- Ch.03-10 - Custom Writable Implementation | Map Reduce | Hadoop18:04
- Ch.03-11 - Custom Partitioner | Map Reduce | Hadoop17:37
- Ch.03-12 - Secondary Sort - Part 1 | Map Reduce | Hadoop19:00
- Ch.03-13 - Secondary Sort - Part 2 | Map Reduce | Hadoop13:32
- Ch.03-14 - Reduce Side Join | Map Reduce | Hadoop23:57
- Ch.03-15 -Map Side Join | Map Reduce | Hadoop09:58
- Ch.03-16 - Hadoop Filesystems and CLI | Hadoop21:08
- Ch.03-17 - Anatomy of a File Read and Write | HDFS | Hadoop20:21
- Ch.03-18 - Introduction to Apache Hive | Hive | Hadoop13:02
- Ch.03-19- Apache Hive vs Traditional RDBMS | Hive | Hadoop13:17
- Ch.03-20- Apache Hive Architecture | Hive | Hadoop19:55
- Ch.03-21- Query Execution Flow | Hive | Hadoop05:55
- Ch.03-22- Table Format | Hive | Hadoop10:58
- Ch.03-23- Hive Database | Hive | Hadoop09:44
- Ch.03-24- Hive Tables | Hive | Hadoop37:58
- Ch.03-25- Hive Demo | Hive | Hadoop17:29
- Ch.04-01: Introduction to Apache Spark06:16
- Ch.04-02: Python Vs. Scala10:46
- Ch.04-03: Introduction to Apache Spark10:21
- Ch.04-04: About Databricks08:02
- Ch.04-05: Spark In The Data Platforms06:27
- Ch.04-06: Running Spark02:30
- Ch.04-07: Demo: Running Spark on Linux Ubuntu05:05
- Ch.04-08: Demo: Running Spark on MacOS03:36
- Ch.04-09: Demo: Running Spark on Windows09:08
- Ch.04-10: Demo: Running Spark on Databricks05:19
- Ch.04-11: From Map Reduce To Spark06:08
- Ch.04-12: Spark Characteristics10:28
- Ch.04-13: Spark Applications03:03
- Ch.04-14: Spark Driver08:09
- Ch.04-15: Spark Session07:45
- Ch.04-16: Spark Cluster Manager05:22
- Ch.04-17: Spark Execution Mode08:09
- Ch.04-18: Spark Executors03:04
- Ch.04-19: Spark Data Partitioning06:31
- Ch.04-20: Spark Operations17:41
- Ch.04-21: Transformations Narrow Vs Wide06:57
- Ch.04-22: Demo: Immutability In Spark06:44
- Ch.04-23: Demo: RDD Text Manipulation03:48
- Ch.04-24: Demo: GroupByKey Vs. ReduceByKey06:57
- Ch.04-25: Demo: Joining RDDs19:17
- Ch.04-26: Demo: Spark RDD APIs21:15
- Ch.04-27: Demo: Repartition Vs. Coalesce17:05
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