The Software Reference Architecture for any Big Data System
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What you'll learn
- Understand the core components of any robust big data architecture for efficient data processing and analytics.
- Learn to design scalable and secure data pipelines using popular big data tools and technologies.
- Gain expertise in integrating diverse data sources into a unified and well-structured big data ecosystem.
- Understand Big Data Reference Architecture Components from Data Sources to Data Consumers
- Become a successful Big Data Architect and Data Engineer
- Learn how to design a performant, scalable distributed system that handles big data.
- Practice Big Data software engineering fundamentals; Data Ingestion, Data Loading & preprocessing, ETL, Batch & Stream processing, Analytic Engine, Visualizion
- Architect and create a big data or distributed system based on ultimate reference architecture
- How Big data architectures can be set up in a generic and repetitive way
- Work out a blueprint for a Big data architecture for any project in any industry landscapse
- Familiarity with big data storage systems: Data Lake, Warehouse, NoSQL & Relational Databases, data mesh and how to best apply it
- Master the Big Data conceptual model with views and activities performed by the functional components
- Big Data architecture High-level and Low-level overview
- Ability to design, implement, and maintain any big data architecture that meets the organization’s requirements
- Understanding of Big Data Security and Privacy
- Understand the role of System Workload Orchestrator and Data Life Cycle management for the Big Data Software Application pipeline
Requirements
- Basic Knowledge of Big Data and data Architecture terminology
- Desire to master Big Data and Become Big Data Architect Expert
- Basic knowledge of data concepts and computer systems will be helpful
- This course welcomes learners from diverse backgrounds.
This is the Only updated Big Data System Reference Architecture Course in The World
The Comprehensive Guide to Designing and Customizing Scalable Big Data Architecture and Mastering Data Architecture
Welcome to "The Ultimate Big Data Reference Architecture" course, where we empower you to become a proficient Big Data Architect and Engineer!
Our course stands out with a remarkable feature - a general and standardized Big Data Architecture model. This unique approach provides logical support for any Big Data architecture, adaptable to various business and deployment models. You'll gain a skill set applicable across industries, from healthcare and finance to e-commerce and more.
Unlike other courses, we go beyond technical tools and technologies. Our goal is to cultivate Big Data Architects and Engineers, empowering you to design robust, scalable, and efficient Big Data solutions. You'll master the underlying principles, strategic decision-making, and architecture design, not just technical execution and coding.
In this Course, we will cover the following:
- The 4 Vs of Big Data : Volume , Velocity , Variety and Variability ( + Value)
- The importance of a Big Data Strandard Reference Architecture for the sucess of any project
- the keys of a robust Big data System : Scalability, Reliability and Performance
- High Level Big Data Reference architecture Overview including the main components :
- Big Data Sources ( Data Provider, Different types of data sources , data noise challenge)
- Big Data Software Application pipeline
- Big Data Ingestion (batch & stream ingestion, Temporary Data Stores)
- Data Loading and preprocessing ( Extract Transform Load - ETL / ELT)
- Big Data Distributed processing ( Batch vs Stream processing , Data Cleaning , data transformation, parallel and distributed computing , Mapreduce )
- Analytics engines ( Descriptive vs Predictive vs Prescriptive Analysis, Machine Learning and Artificial Intelligence)
- Loading
- Visualization ( Static vs Dynamic Data Visualization, Serving Data Storage)
- Workload orchestrator (conductor and manager of tasks in Big data system ")
- Data Life Cycle management
- Big Data IT Infrastructure ( Data Storage, Computing , Networking & System Ressources Management, Horizontal vs Scaling)
- Big Data Security and privacy
- Big Data Consumers / End Users and Stakeholders
- Low Level Big Data Reference architecture Overview including the main components :
- Different types of Software Big data Architecture : Lambda, Kappa and Microservices
- Big Data Architecture Layers
- Data Sources : Data Types structured vs semistructured vs unstructured data
- Data Ingestion / collection : Apache Kafka , Apache Flume , Amazon Kinesis Data Streams
- Big Data Storage : Data Lakes, Data Warehouses, NoSQL & SQL DataBases
- Big Data Batch and Stream Distributed Processing : Hadoop Mapreduce Apache Spark, Apache Flink , Storm
- Big Data Querying : Apache Hive , Apache PIG, Presto
- System Workload Orchestrator : Apache Airflow , Luigi , Apache Oozie
- Data Visualization: Real Time vs Static Dashboards, Kibana, Apache Zeppelin, Superset,
- Additional Lecture: Data Mesh for Big Data Cloud Computing & Infrastructure
What You'll Learn:
- Understand the universally applicable Big Data Reference Architecture, adaptable to diverse industries and business models.
- Learn the art of designing efficient, scalable, and future-proof Big Data solutions, addressing real-world challenges.
- Gain proficiency in architecting Big Data systems with a strong focus on performance, security, and data governance.
- Master strategic decision-making for selecting and integrating the right technologies, tools, and frameworks.
- Explore the logical support provided by the standardized architecture, enabling seamless integration across domains.
- Develop a deep understanding of data flow, orchestration, and lifecycle management within Big Data systems
Our Approach: We believe in elevating you beyond technical developers. Our course fosters the mindset of Big Data Architects and Engineers, empowering you to design cutting-edge solutions.
You'll gain a holistic understanding of Big Data architecture.
In this course, you will learn the low-level details of the Big Data software application pipeline. You will learn about the technologies and tools that are used to implement each stage of the pipeline, and you will gain a comprehensive understanding of Big Data architecture. By the end of this course, you will be able to design and implement your own Big Data solutions.
This course is perfect for anyone who wants to become a Big Data Architect or Engineer. Whether you are a seasoned professional or a beginner, this course will give you the skills you need to succeed in the field of Big Data.
Embrace the future of Big Data architecture and unlock endless possibilities. Enroll now and embark on a transformative journey with "The Ultimate Big Data Reference Architecture" course!
PLEASE NOTE: This is not a technichal course of any tools or frameworks (Spark/Hadoop/Kafka ... ).
Enroll today and start learning!
Who this course is for:
- Big Data Architect
- Big Data Scientists
- Enterprise IT Architects
- Big Data Engineers
- Data Architects or Software Engineers who want to master Big Data Architecture
- Anyone interested in Data Architecture or Big data Systems Design
- Data Scientists
- Data Engineers
- Data Developpers
- Aspiring Big Data Architects looking to design scalable and adaptable solutions across various industries.
- Data Engineers and IT professionals aiming to elevate their skill set to architect-level in Big Data projects.
- Business strategists and decision-makers interested in understanding the foundations of Big Data architecture
- Software Engineers and Data Scientists seeking to broaden their expertise in Big Data solution design.
