What will you learn in Big Data Architect Masters Program
Gain a strong foundation in big data technologies including Hadoop, Spark, and Kafka
Master data processing, data engineering, and data warehousing at scale
Learn to design real-time, batch, and streaming architectures
Work with tools like Hive, HBase, Pig, Sqoop, Flume, and NoSQL databases
Prepare for high-level roles in data architecture, engineering, and analytics
Program Overview
Module 1: Big Data Hadoop Certification Training
⏳ 3 weeks
Topics: HDFS, MapReduce, YARN, Hive, Pig, HBase
Hands-on: Perform ETL operations using Hadoop ecosystem tools
Module 2: Apache Spark and Scala Certification Training
⏳ 2 weeks
Topics: RDDs, DataFrames, Spark SQL, MLlib, Spark Streaming
Hands-on: Build real-time and batch processing pipelines using Spark
Module 3: Apache Kafka Certification Training
⏳ 1 week
Topics: Kafka architecture, producers, consumers, partitions, brokers
Hands-on: Develop Kafka-based event streaming applications
Module 4: Talend for Data Integration
⏳ 2 weeks
Topics: ETL basics, Talend components, job design
Hands-on: Design Talend jobs for batch data processing and integration
Module 5: Apache Cassandra Certification Training
⏳ 1 week
Topics: NoSQL concepts, data modeling, replication, consistency
Hands-on: Store and query large-scale structured data with Cassandra
Module 6: MongoDB Certification Training
⏳ 1 week
Topics: CRUD, aggregation, indexing, replication, sharding
Hands-on: Build flexible schema applications with MongoDB
Module 7: Data Warehousing with Amazon Redshift
⏳ 1 week
Topics: AWS Redshift architecture, Spectrum, best practices
Hands-on: Create and manage data warehouses on AWS Redshift
Module 8: Azure Data Factory
⏳ 1 week
Topics: Data pipelines, triggers, activities, linked services
Hands-on: Automate data movement and transformation in Azure
Module 9: Capstone Project
⏳ 2 weeks
Topics: End-to-end big data architecture design
Hands-on: Implement a real-world project using Hadoop, Spark, and NoSQL
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Job Outlook
Big data architecture is among the most in-demand roles in tech
Job titles include Big Data Architect, Data Engineer, Cloud Data Engineer
Salary potential: $120,000 to $180,000+ depending on experience and location
High demand in fintech, healthcare, retail, telecom, and SaaS companies
Explore More Learning Paths
Expand your expertise in large-scale data systems and strengthen your ability to design, manage, and optimize modern data architectures with these hand-picked big data learning programs.
Related Courses
Big Data Specialization Course – Build a strong foundation in distributed systems, data mining, and big data analytics for real-world applications.
Big Data Integration and Processing Course – Master ETL pipelines, data lakes, and processing frameworks essential for enterprise-level data engineering.
Data Engineering, Big Data, and Machine Learning on GCP Specialization Course – Learn to design scalable data pipelines and machine learning workflows using Google Cloud Platform.
Related Reading
Gain deeper insight into how project management drives real-world success:
What Is Project Management? – Understand the principles that make every great project a success story.
Specification: Big Data Architect Masters Program Course
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FAQs
- The program starts with foundational modules like Hadoop and SQL.
- No prior Big Data experience is required.
- Programming basics in Python or Java are helpful but optional.
- Beginner-friendly labs and guided projects support learning by doing.
- Ideal for career changers entering data architecture or engineering fields.
- Includes end-to-end architecture projects from ingestion to visualization.
- Covers Hadoop, Spark, Hive, Kafka, and cloud data solutions.
- Teaches scalability, fault tolerance, and optimization principles.
- Involves capstone projects simulating enterprise Big Data environments.
- Builds both design and hands-on implementation expertise.
- Learn Hadoop ecosystem tools: HDFS, MapReduce, Hive, Pig.
- Get hands-on with Apache Spark and real-time processing using Kafka.
- Explore NoSQL databases like Cassandra and MongoDB.
- Learn cloud data platforms like AWS and Azure Data Lake.
- Gain exposure to orchestration and pipeline automation tools.
- Build data ingestion pipelines using Kafka and Flume.
- Process and clean datasets using Spark and Hive.
- Implement a data warehouse on AWS or Azure.
- Create dashboards integrating processed data in visualization tools.
- Capstone project involves a full Big Data architecture design.
- Qualifies for roles like Big Data Architect or Data Engineer.
- Opens opportunities as Cloud Data Specialist or ETL Developer.
- Builds foundation for Machine Learning and AI data pipeline roles.
- Enhances credentials for enterprise data consultancy positions.
- Global demand ensures competitive salary and career growth.
