BIG DATA MASTER
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Course sections
Section 1
Introduction to Big Data
1
Overview of Big Data
2
Key characteristics of Big Data
3
Understanding the challenges of Big Data
Section 2
Data Storage and Processing
1
Data storage systems (HDFS, NoSQL databases)
2
Data processing frameworks (MapReduce, Spark)
3
Distributed computing architecture
Section 3
Data Analysis
1
Data mining techniques
2
Data visualization and exploration tools
3
Machine learning algorithms for Big Data analysis
Section 4
Data Integration and Transformation
1
Extracting data from various sources
2
Data transformation and cleaning
3
Data integration techniques (ETL)
Section 5
Big Data Technologies
1
Hadoop ecosystem (Hive, Pig, HBase, Mahout)
2
Spark ecosystem (Spark SQL, MLlib, GraphX)
3
Real-time data processing systems (Kafka, Storm)
Section 6
Cloud Computing for Big Data
1
Cloud computing architecture (AWS, Azure, Google Cloud)
2
Cloud-based data storage and processing
Section 7
Section 8
1
Data security and privacy concerns in cloud-based environments
Section 9
Big Data Applications
1
Big Data in healthcare, finance, retail, and other industries
2
IoT and Big Data
3
Big Data for predictive analytics and decision-making
Section 10
Big Data Management
1
Big Data project management
2
Agile methodologies for Big Data projects
3
Team management and collaboration
Section 11
Emerging Trends in Big Data
1
Edge computing and Big Data
2
Blockchain and Big Data
3
Quantum computing and Big Data
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Big Data Technologies
Real-time data processing systems (Kafka, Storm)
Lesson is locked. Please Buy course to proceed.
Big Data Technologies
Spark ecosystem (Spark SQL, MLlib, GraphX)
Complete
Cloud Computing for Big Data
Cloud computing architecture (AWS, Azure, Google Cloud)
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