Published 4/2023 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz Language: English | Size: 1.82 GB | Duration: 6h 33m Analyze, Design and Build scalable, resilient and cost-effective Big Data pipelines with a methodical process
Free DownloadWhat you'll learn Learn about the building blocks of a big data pipeline, their functions and challenges Adapt an end-to-end methodical approach to designing a big data pipeline Explore techniques to ensure overall scaling of a big data pipeline Study design patterns for building blocks, their advantages, shortcomings, applications and available technologies Focus additionally on Infrastructure, Operations and Security for Big Data deployments Exercise the learnings in the course with a Batch and Realtime use case study Requirements Big Data Technology Concepts Familiarity with Big Data Technologies like Apache Spark, Apache Kafka and NoSQL Development / Deployment Experience with Big Data Technologies and Pipelines Software Design and Development Experience including Cloud & Microservices Description Big data technologies have been growing exponentially over the past few years and have penetrated into every domain and industry in software development. It has become a core skill for a software engineer. Robust and effective big data pipelines are needed to support the growing volume of data and applications in the big data world. These pipelines have become business critical and help increase revenues and reduce cost.Do quality big data pipelines happen by magic? High quality designs that are scalable, reliable and cost effective are needed to build and maintain these pipelines.How do you build an end-to-end big data pipeline that leverages big data technologies and practices effectively to solve business problems? How do you integrate them in a scalable and reliable manner? How do you deploy, secure and operate them? How do you look at the overall forest and not just the individual trees? This course focuses on this skill gap.What are the topics covered in this course?We start off by discussing the building blocks of big data pipelines, their functions and challenges.We introduce a structured design process for building big data pipelines.We then discuss individual building blocks, focusing on the design patterns available, their advantages, shortcomings, use cases and available technologies.We recommend several best practices across the course.We finally implement two use cases for illustration on how to apply the learnings in the course to a real world problem. One is a batch use case and another is a real time use case. Overview Section 1: Introduction & Expectations Lecture 1 Need for Quality Pipeline Design Lecture 2 Course Coverage and Pre-requisites Lecture 3 Cloud Serverless Technologies Section 2: Building Blocks for Big Data Pipelines Lecture 4 The Big Data Pipeline Network Lecture 5 Data Acquisition Blocks Lecture 6 Data Transport Blocks Lecture 7 Data Processing Blocks Lecture 8 Data Storage Blocks Lecture 9 Data Serving Blocks Lecture 10 Data Pipeline Infrastructure Lecture 11 Data Pipeline Operations Section 3: System Design Process Lecture 12 System Design Process Overview Lecture 13 Analyze Functional Requirements Lecture 14 Analyze Pipeline Input Lecture 15 Analyze Non-functional Requirements Lecture 16 Draw a Pipeline Flowchart Lecture 17 Create a Skeleton Design Lecture 18 Analyze Scaling Lecture 19 Select Technologies Lecture 20 Design Infrastructure and Operations Lecture 21 Develop a Test Strategy Section 4: Scalable Pipelines - Design Principles Lecture 22 Batch vs Realtime Pipelines Lecture 23 Distributed Architectures Lecture 24 Microservices based Architectures Lecture 25 Batch Pipelines - Best Practices Lecture 26 Realtime Pipelines - Best Practices Lecture 27 Performance Benchmarking for Big Data Pipelines Section 5: Data Acquisition Design Lecture 28 File Transfer Pattern Lecture 29 Extraction Client Pattern Lecture 30 Ingestion API Pattern Lecture 31 Pub Sub Acquisition Pattern Lecture 32 Data Acquisition Design Practices Section 6: Data Transport Design Lecture 33 Extract Load Pattern Lecture 34 Request Response Pattern Lecture 35 Event Streaming Pattern Lecture 36 Data Transport Design Practices Section 7: Data Processing & Transformation Design Lecture 37 Data Processing Patterns Lecture 38 Distributed Processing with Big Data Lecture 39 Batch Processing Design Practices - Part 1 Lecture 40 Batch Processing Design Practices - Part 2 Lecture 41 Stream Processing Design Practices Lecture 42 Batch vs Realtime Processing Lecture 43 Input and Output Considerations for Processing Lecture 44 Processing Engine Technologies Section 8: Storage Design Lecture 45 Distributed File System Pattern Lecture 46 Relational Database Pattern Lecture 47 Document Database Pattern Lecture 48 Columnar Database Pattern Lecture 49 Graph Database Pattern Lecture 50 Distributed Cache Pattern Lecture 51 Data Storage Design Practices - 1 Lecture 52 Data Storage Design Practices - 2 Section 9: Serving Design Lecture 53 Query Interface Pattern Lecture 54 Serving API Pattern Lecture 55 Push Client Pattern Lecture 56 Publish Subscribe Pattern Lecture 57 Data Serving Design Practices Section 10: Infrastructure and Deployments Lecture 58 Infrastructure Technologies Lecture 59 Microservices Deployments Lecture 60 Processing Jobs Deployments Lecture 61 Databases and Queues Deployments Lecture 62 Geographical Distribution Section 11: Security Lecture 63 Pipeline Security by Design Lecture 64 Secure External Interfaces Lecture 65 Secure Data Storage Lecture 66 Privacy Considerations Lecture 67 Multi-Tenancy Considerations Section 12: Serviceability Lecture 68 Elements of Serviceability Lecture 69 Monitoring Pipelines Lecture 70 Data to Monitor Lecture 71 Pipeline Troubleshooting Section 13: Use Case I : Customer Journey Analytics (CJA) Lecture 72 Problem Definition for CJA Lecture 73 Study CJA Functional Requirements Lecture 74 Analyze CJA Input Data Lecture 75 Study CJA Non-Functional Requirements Lecture 76 Study CJA Pipeline Flowchart Lecture 77 Create CJA Skeleton Design Lecture 78 Analyze CJA Scaling Lecture 79 Select Technologies for CJA Lecture 80 Design Infrastructure and Operations for CJA Section 14: Use Case II : Suspicious Login Alerting (SLA) Lecture 81 Problem Definition for SLA Lecture 82 Study SLA Functional Requirements Lecture 83 Analyze SLA Input Data Lecture 84 Study SLA Non-Functional Requirements Lecture 85 Draw SLA Pipeline Flowchart Lecture 86 Create SLA Skeleton Design Lecture 87 Analyze SLA Scaling Lecture 88 Select SLA Technologies Lecture 89 Define SLA Infrastructure and Operations Section 15: Conclusion Lecture 90 Thank You Big Data Pipeline Designers & Architects,Big Data Developers looking to move into Design/Architecture roles,Software Architects looking to gain Big Data Experience