Big Data For Architects

This course not only covers all the basic Big Data tools and technologies but also covers the in detail differentiation between the same set of technologies.

$14.95 / MONTH SITE SUBSCRIPTION (W/ 14 DAY FREE TRIAL) $149.95 / YEAR SITE SUBSCRIPTION (W/ 14 DAY FREE TRIAL)

Course curriculum

1. About this course: Overview, Learning Outcomes, Who Should Enroll...
1. Segment - 01 - Course Structure and Approach
2. Segment - 02 - Pre-requisites
3. Segment - 03 - Course Audience
4. Segment - 04 - About Instructor
1. Segment - 05 - Google Cloud Account Setup
2. Segment - 06 - Creating a Dataproc Cluster
3. Segment - 07 - GCP Account Best Practices
4. Installation DataProc cluster
1. Segment - 08 - Big Data Logical Architecture
2. Segment - 09 - Evolution of Big Data Technologies
3. Segment - 10 - Key Big Data Architectures
4. Segment - 11 - Typical Big Data Batch Pipeline
5. Segment - 12 - Typical Big Data Streaming Pipeline
6. Segment - 13 - Bonus 1 - Another Example of Big Data Streaming Pipeline
7. Segment - 14 - Bonus 2 - Another Example of Big Data Streaming Pipeline
1. Segment - 15 - Factors to consider while comparing Ingestion frameworks
2. Segment - 16 - Kafka vs Flume
3. Segment - 17 - NiFi vs Kafka
4. Segment - 18 - Sqoop vs Flume
5. Segment - 19 - Sqoop vs Kafka Connect
6. Segment - 20 - Hands-on NiFi Installation
7. Segment - 21 - Hands-on Kafka Installation
8. Segment - 22 - Hands-on Kafka and NiFi Integration Background
9. Segment - 23 - Hands-on Kafka and NiFi Integration
1. Segment - 24 - Factors to consider while comparing Storage frameworks
2. Segment - 25 - HDFS vs HBase
3. Segment - 26 - HBase vs Kudu
4. Segment - 27 - HDFS vs Kudu
5. Segment - 28 - HBase vs Cassandra
1. Segment - 29 - Text vs Binary
2. Segment - 30 - Interoperability
3. Segment - 31 - Row Oriented vs Column Oriented
4. Segment - 32 - Splittable Formats
5. Segment - 33 - Schema Evolution
6. Segment - 34 - Comparing Data Formats
7. Segment - 35 - Hands-on Sqoop Installation on Dataproc Cluster
8. Segment - 36 - Hands-on Big Data Batch Pipeline Use Avro Format
1. Segment - 37 - Factors to consider while comparing Processing frameworks
2. Segment - 38 - MR vs Spark Logical Architecture Perspective
3. Segment - 39 - MR vs Spark Performance Perspective
4. Segment - 40 - Spark vs Tez
5. Segment - 41 - Spark vs Flink
6. Segment - 42 - Kafka Streams vs Spark Streaming
7. Segment - 43 - Spark 2.x Streaming vs Spark 1.x Streaming
8. Segment - 44 - Spark Core vs Spark SQL
9. Segment - 45 - Hands-on Kafka & Spark Streaming Integration
1. Segment - 46 - Factors to consider while comparing Analysis frameworks
2. Segment - 47 - Hive vs Impala
3. Segment - 48 - Hive vs Pig
4. Segment - 49 - Hive vs Spark SQL
5. Segment - 50 - Hive vs Hive LLAP vs Impala
6. Segment - 51 - Hive vs KSQL
7. Segment - 52 - 7. KSQL vs KSQLDB
8. Segment - 53 - Hands-on KSQL
9. Segment - 54 - Hands-on Write to a Stream and Table using KSQL
10. Segment - 55 - Hands-on Streaming ETL Pipeline Background
11. Segment - 56 - Hands-on Build a Scalable ETL Pipeline with Kafka Connect - part 1
12. Segment - 57 - Hands-on Build a Scalable ETL Pipeline with Kafka Connect - part 2
1. Segment - 58 - Delta Architecture
2. Segment - 59 - Why Delta Lake?
3. Segment - 60 - Challenges with Data Lake
4. Segment - 61 - Delta Lake Demo
1. Segment - 62 - Solr vs ElasticSearch
2. Segment - 63 - Cloudera Search vs Solr
3. Segment - 64 - Oozie vs Airflow
4. Segment - 65 - KSQL vs KStreams
1. Segment - 66 - Conclusion

About this course

Free
68 lessons
8.5 hours of video content

Big Data For Architects

Course curriculum

Welcome to the course!

Module 1: Course Overview

Module 2: Environment Setup

Module 3: Holistic View, Architectures and Pipelines

Module 4: Key Ingestion-Data Flow Frameworks

Module 5: Key Storage Frameworks

Module 6: Data formats

Module 7: Key Data Processing Frameworks

Module 8: Key Data Analysis Frameworks

Module 9: Delta Lake

Module 10: Bonus

Module 11: Epilogue

About this course