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  • Lesson.No : 01
  • 00:00:09

  • Big Data Engineering In Depth Promo

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Course Lessons

  1. 1- Big Data Engineering In Depth Promo
  2. 2- Ch.01-01 Course Introduction
  3. 3- Ch.01-02 Getting the max benefit from this course
  4. 4- Ch.01-03 Assignments, Labs, and Textbooks
  5. 5- Ch.01-04 Course Content Overview
  6. 6- Ch.02-01 Introduction To Data Management
  7. 7- Ch.02-02 Data Abstraction
  8. 8- Ch.02-03 Physical Layer
  9. 9- Ch.02-04 Logical Layer
  10. 10- Ch.02-05 View Layer
  11. 11- Ch.02-06 Data Solution Thinking
  12. 12- Ch.02-07 Introduction to DWH
  13. 13- Ch.02-08 DWH Vs Transactional DB
  14. 14- Ch.02-09 DWH BusinessTypes
  15. 15- Ch.02-10 Use Cases For DWH Types and Transactional DB
  16. 16- Ch.02-11 Multi Temperature Storage System
  17. 17- Ch.02-12 DWH Characteristics and Architecture Components DWH Architecture
  18. 18- Ch.02-13 Source Systems Integration Process DWH Architecture
  19. 19- Ch.02-14 Source Systems Extraction Layer DWH Architecture
  20. 20- Ch.02-15 Staging Layer DWH Architecture
  21. 21- Ch.02-16 Data Modeling DWH Architecture
  22. 22- Ch.02-17 Dimension Types: Conformed Dimension Data Modeling DWH Architecture
  23. 23- Ch.02-18 Dimension Types: Degenerate Dimension Data Modeling DWH Architecture
  24. 24- Ch.02-19 Dimension Types: Junk Dimension Data Modeling DWH Architecture
  25. 25- Ch.02-20 Dimension Types: Role Playing Dimension Data Modeling DWH Architecture
  26. 26- Ch.02-21 Dimension Types: Outrigger Dimension Data Modeling DWH Architecture
  27. 27- Ch.02-22 Dimension Types: Snowflake Dimension Data Modeling DWH Architecture
  28. 28- Ch.02-23 Dimension Types: Slowly changing dimension SCD 0,1,2,3,4 Data Modeling DWH Architecture
  29. 29- Ch.02-24 Dimension Types: Fast Changing Dimensions Data Modeling DWH Architecture
  30. 30- Ch.02-25 Dimension Types: Shrunken Dimension Data Modeling DWH Architecture
  31. 31- Ch.02-26 Dimension Types: Multi Valued Dimension Data Modeling DWH Architecture
  32. 32- Ch.02-28 Dimension Types: Heterogeneous Dimension Data Modeling DWH Architecture
  33. 33- Ch.02-27 Dimension Types: Swappable Dimension Data Modeling DWH Architecture
  34. 34- Ch.02-29 Fact Tables Data Modeling DWH Architecture
  35. 35- Ch.02-30 Schema Types Data Modeling DWH Architecture
  36. 36- Ch.02-31 Introduction ETL DWH Architecture
  37. 37- Ch.02-32 Best Practices ETL DWH Architecture
  38. 38- Ch.02-33 Surrogate Vs Natural Key Data Modeling
  39. 39- Ch.02-34 Partitioning vs Bucketing Data Modeling
  40. 40- Ch.02-35 Kimball vs Inmon Data Modeling
  41. 41- Ch.03-01 Introduction To Distributed Systems Hadoop
  42. 42- Ch.03-02 Introduction To Distributed Systems Hadoop
  43. 43- Ch.03-03 Introduction To Hadoop
  44. 44- Ch.03-04 HDFS Hadoop
  45. 45- Ch.03-05 YARN Hadoop
  46. 46- Ch.03-06 - Map Reduce Hadoop
  47. 47- Ch.03-07 - Combiner Map Reduce Hadoop
  48. 48- Ch.03-08 - With vs Without Combiners Map Reduce Hadoop
  49. 49- Ch.03-09 - Inverted Index Map Reduce Hadoop
  50. 50- Ch.03-10 - Custom Writable Implementation Map Reduce Hadoop
  51. 51- Ch.03-11 - Custom Partitioner Map Reduce Hadoop
  52. 52- Ch.03-12 - Secondary Sort - Part 1 Map Reduce Hadoop
  53. 53- Ch.03-13 - Secondary Sort - Part 2 Map Reduce Hadoop
  54. 54- Ch.03-14 - Reduce Side Join Map Reduce Hadoop
  55. 55- Ch.03-15 -Map Side Join Map Reduce Hadoop
  56. 56- Ch.03-16 - Hadoop Filesystems and CLI Hadoop
  57. 57- Ch.03-17 - Anatomy of a File Read and Write HDFS Hadoop
  58. 58- Ch.03-18 - Introduction to Apache Hive Hive Hadoop
  59. 59- Ch.03-19- Apache Hive vs Traditional RDBMS Hive Hadoop
  60. 60- Ch.03-20- Apache Hive Architecture Hive Hadoop
  61. 61- Ch.03-21- Query Execution Flow Hive Hadoop
  62. 62- Ch.03-22- Table Format Hive Hadoop
  63. 63- Ch.03-23- Hive Database Hive Hadoop
  64. 64- Ch.03-24- Hive Tables Hive Hadoop
  65. 65- Ch.03-25- Hive Demo Hive Hadoop
  66. 66- Ch.04-01: Introduction to Apache Spark
  67. 67- Ch.04-02: Python Vs. Scala
  68. 68- Ch.04-03: Introduction to Apache Spark
  69. 69- Ch.04-04: About Databricks
  70. 70- Ch.04-05: Spark In The Data Platforms
  71. 71- Ch.04-06: Running Spark
  72. 72- Ch.04-07: Demo: Running Spark on Linux Ubuntu
  73. 73- Ch.04-08: Demo: Running Spark on MacOS
  74. 74- Ch.04-09: Demo: Running Spark on Windows
  75. 75- Ch.04-10: Demo: Running Spark on Databricks
  76. 76- Ch.04-11: From Map Reduce To Spark
  77. 77- Ch.04-12: Spark Characteristics
  78. 78- Ch.04-13: Spark Applications
  79. 79- Ch.04-14: Spark Driver
  80. 80- Ch.04-15: Spark Session
  81. 81- Ch.04-16: Spark Cluster Manager
  82. 82- Ch.04-17: Spark Execution Mode
  83. 83- Ch.04-18: Spark Executors
  84. 84- Ch.04-19: Spark Data Partitioning
  85. 85- Ch.04-20: Spark Operations
  86. 86- Ch.04-21: Transformations Narrow Vs Wide
  87. 87- Ch.04-22: Demo: Immutability In Spark
  88. 88- Ch.04-23: Demo: RDD Text Manipulation
  89. 89- Ch.04-24: Demo: GroupByKey Vs. ReduceByKey
  90. 90- Ch.04-25: Demo: Joining RDDs
  91. 91- Ch.04-26: Demo: Spark RDD APIs
  92. 92- Ch.04-27: Demo: Repartition Vs. Coalesce