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Advanced Big Data Program!

Explore advanced data processing techniques, including batch processing with frameworks like Apache Spark and stream processing with Apache Flink, enhancing your ability to handle large-scale data efficiently!

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5.0
3,720 students

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₹45,000 ₹90,000
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  • Course MajorHadoop Ecosystem
  • Course MajorApache Spark
  • Course MajorNoSQL Databases
  • Course MajorApache Kafka
  • Course MajorTensorFlow
  • Course MajorTableau
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What you'll learn

Advanced Data Processing Techniques

Explore advanced data processing techniques, including batch processing with frameworks like Apache Spark and stream processing with Apache Flink, enhancing your ability to handle large-scale data efficiently.

Distributed Computing Architectures

Gain insights into distributed computing architectures such as Hadoop and Apache HBase, understanding how these frameworks enable scalable storage and processing of big data across clusters of computers.

Big Data Analytics and Machine Learning

Learn how to leverage big data analytics and machine learning algorithms to derive valuable insights from massive datasets, including techniques for data exploration, feature engineering, and model training at scale.

Data Engineering Best Practices

Understand data engineering best practices, including data ingestion, transformation, and storage in distributed environments, ensuring data reliability, scalability, and performance.

Real-time Data Processing

Dive into real-time data processing technologies like Apache Kafka and Apache Storm, mastering the ability to process and analyze streaming data in real-time for immediate insights and actions.

Big Data Security and Governance

Explore the intricacies of big data security and governance, including data privacy, access control, and compliance considerations, ensuring the integrity and confidentiality of your data assets in large-scale deployments.

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Course Content

  • Overview of Big Data Concepts and Challenges
  • Evolution of Big Data Technologies
  • Real-world Applications of Big Data
  • Introduction to Distributed Computing

  • Introduction to Apache Spark
  • Spark Architecture and Components
  • Spark RDDs, DataFrames, and Datasets
  • Advanced Spark Transformations and Actions
  • Spark SQL and Data Manipulation
  • Performance Optimization Techniques in Spark

  • Overview of Hadoop Ecosystem
  • Hadoop Distributed File System (HDFS)
  • MapReduce Programming Model
  • Introduction to Apache HBase
  • HBase Data Model and Architecture
  • HBase Administration and Performance Tuning

  • Introduction to Big Data Analytics
  • Data Exploration and Visualization Techniques
  • Feature Engineering for Big Data
  • Machine Learning with Big Data
  • Distributed Model Training and Evaluation
  • Advanced Machine Learning Algorithms for Big Data

  • Introduction to Stream Processing
  • Apache Kafka Fundamentals
  • Kafka Architecture and Components
  • Stream Processing with Apache Storm
  • Real-time Analytics and Monitoring
  • Integrating Stream Processing with Batch Processing

  • Data Ingestion Techniques for Big Data
  • Introduction to NoSQL Databases
  • Introduction to Data Lakes and Data Warehouses
  • Data Quality and Data Governance
  • Scalable Data Storage Solutions

  • Overview of Big Data Security Challenges
  • Authentication and Authorization in Big Data Systems
  • Data Encryption and Key Management
  • Auditing and Compliance in Big Data Environments
  • Privacy and Data Protection Regulations
  • Implementing Security Best Practices

  • Advanced Data Analysis Techniques
  • Time Series Analysis and Forecasting
  • Graph Analytics for Big Data
  • Geospatial Analysis and Visualization
  • Text Analytics and Natural Language Processing
  • Analyzing Unstructured Data with Big Data Tools

  • Introduction to Cloud Computing and Big Data
  • Cloud-based Big Data Platforms (AWS, Azure, Google Cloud)
  • Deploying Big Data Solutions on Cloud Platforms
  • Managing Big Data Workloads in the Cloud
  • Cost Optimization Strategies for Cloud-based Big Data

  • Introduction to IoT and Edge Computing
  • Challenges and Opportunities of Big Data in IoT
  • Collecting and Processing Big Data from IoT Devices
  • Real-time Analytics at the Edge
  • Integration of Big Data with IoT Platforms
  • Case Studies and Use Cases of Big Data in IoT

  • Introduction to Business Intelligence (BI)
  • Data Warehousing and OLAP Concepts
  • Building Big Data-driven BI Solutions
  • Data Visualization and Dashboards
  • Self-Service BI Tools and Platforms
  • Advanced Analytics for Business Decision Making

  • Introduction to Big Data Project Management
  • Planning and Estimating Big Data Projects
  • Agile and Waterfall Methodologies for Big Data Projects
  • Risk Management and Mitigation Strategies
  • Collaboration and Communication in Big Data Teams
  • Case Studies and Best Practices in Big Data Project Management

  • Infrastructure Requirements for Big Data Systems
  • Scalable Storage Solutions (HDFS, Object Storage)
  • Resource Management and Scheduling (YARN, Mesos)
  • Containerization and Orchestration for Big Data
  • High Availability and Disaster Recovery
  • Monitoring and Performance Tuning

  • Challenges of Big Data Integration
  • Extract, Transform, Load (ETL) Processes
  • Data Integration Platforms and Tools
  • Data Federation and Virtualization
  • Real-time Data Integration Solutions
  • Best Practices for Big Data Interoperability

  • Ethical Considerations in Big Data Analytics
  • Privacy Challenges in Big Data Environments
  • Fairness and Bias in Big Data Algorithms
  • Responsible Data Use and Governance
  • Regulatory Compliance (GDPR, CCPA)
  • Implementing Ethical Guidelines in Big Data Projects

Industry recognized certification

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Instructor

Akash Sharma

The trainer leading the Advanced Big Data Program is a distinguished expert in the field, boasting extensive experience in big data technologies and analytics. With a proven track record of successful implementations across various industries, the trainer brings a wealth of practical insights to the classroom, enriching the learning experience for participants.

Renowned for their dynamic teaching style, the trainer ensures that complex big data concepts are presented in a clear and accessible manner, fostering an environment conducive to active learning and engagement. Their passion for empowering students with the latest industry knowledge and best practices is evident through personalized mentorship and guidance, equipping participants with the skills needed to tackle real-world big data challenges confidently.

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5.0
Course Rating
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Advanced Could Computing Program!
₹45,000 ₹90000