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πŸš€ PrestoDB Training
Distributed SQL Query Analytics & Big Data Processing using PrestoDB

πŸ“˜ What is PrestoDB?

PrestoDB is a powerful open-source distributed SQL query engine used for querying and analyzing large-scale datasets across multiple data sources in real time.

Originally developed by Facebook and now maintained by the Presto Foundation, PrestoDB allows organizations to query data from different systems without moving the data.

PrestoDB is designed for:

  • Big Data analytics
  • Interactive SQL querying
  • Data lake analytics
  • Multi-source data federation
  • Real-time reporting
  • High-speed distributed querying

PrestoDB is known for:

  • High-performance SQL queries
  • Distributed query execution
  • Real-time analytics
  • Multi-source connectivity
  • Scalability
  • Low-latency querying

PrestoDB supports querying across:

  • Hadoop (HDFS)
  • Hive
  • MySQL
  • PostgreSQL
  • MongoDB
  • Cassandra
  • Kafka
  • Cloud storage systems

PrestoDB helps organizations:

  • Analyze Big Data quickly
  • Query multiple databases simultaneously
  • Enable interactive analytics
  • Improve business intelligence
  • Reduce data duplication
  • Build scalable analytics systems

PrestoDB is widely used in:

  • Banking & Finance
  • E-Commerce Platforms
  • Telecom Systems
  • Healthcare Analytics
  • Cloud Data Platforms
  • Enterprise Reporting Systems

Popular technologies used with PrestoDB:

  • SQL
  • Hadoop
  • Hive
  • Spark
  • Kafka
  • Python
  • Docker
  • Kubernetes
  • AWS / Azure / GCP

In simple words:

PrestoDB helps businesses analyze huge datasets from multiple systems instantly using SQL without moving the data.

🎯 Course Overview

This course helps you learn:

  • PrestoDB fundamentals
  • Distributed SQL query processing
  • Big Data analytics
  • Data federation concepts
  • SQL for analytics
  • Data lake querying
  • Performance optimization
  • Cloud deployment
  • Real-time analytics projects
  • Enterprise reporting systems

Learn PrestoDB from beginner to advanced level with practical hands-on Big Data analytics projects.

βš™οΈ How PrestoDB Works

  1. Connect multiple data sources
  2. Run SQL queries across systems
  3. Presto distributes query processing
  4. Fetch & analyze data in real time
  5. Generate reports & analytics
  6. Deliver business insights quickly

Example:
Analyze customer purchase data from MySQL, Hive, and Kafka simultaneously using PrestoDB.

🏒 Real-Time Business Use Cases

Banking

  • Transaction analytics
  • Fraud detection insights

E-Commerce

  • Customer behavior analytics
  • Product recommendation reporting

Healthcare

  • Patient analytics systems
  • Healthcare reporting

Telecom

  • Network performance analytics
  • Customer usage reports

Enterprise Reporting

  • Multi-source business intelligence
  • Unified analytics dashboards

πŸ“š DETAILED COURSE CONTENT

Module 1: Introduction to PrestoDB

  • What is PrestoDB
  • Features of PrestoDB
  • PrestoDB architecture
  • Distributed SQL query engine basics
  • PrestoDB use cases
  • Installation & setup

Module 2: Big Data & Analytics Fundamentals

  • Big Data basics
  • Distributed systems overview
  • Data warehousing concepts
  • Interactive analytics basics
  • Data federation concepts

Module 3: PrestoDB Architecture

  • Coordinator node
  • Worker nodes
  • Query execution workflow
  • Distributed query engine basics
  • Cluster communication

Module 4: Installation & Environment Setup

  • Installing PrestoDB
  • Environment setup
  • Cluster setup basics
  • Configuration management
  • Running Presto queries

Module 5: SQL Fundamentals for PrestoDB

  • SQL basics
  • SELECT statements
  • Filtering & sorting
  • Joins & aggregations
  • Advanced SQL queries

Module 6: Querying Multiple Data Sources

  • Connecting Hive
  • MySQL integration
  • PostgreSQL integration
  • MongoDB basics
  • Cassandra integration overview

Module 7: Data Federation Concepts

  • What is data federation
  • Multi-source querying
  • Federated query processing
  • Unified analytics concepts

Module 8: Hive & Hadoop Integration

  • Hive basics
  • Hadoop integration
  • HDFS querying basics
  • Big Data analytics workflows

Module 9: Kafka Integration

  • Kafka basics
  • Streaming analytics concepts
  • Querying streaming data
  • Real-time event analytics

Module 10: Data Lake Analytics

  • What is a data lake
  • Querying cloud storage
  • S3 integration basics
  • Enterprise data lake concepts

Module 11: Performance Optimization

  • Query optimization
  • Memory tuning basics
  • Parallel query execution
  • Resource management
  • Performance monitoring

Module 12: Security in PrestoDB

  • Authentication basics
  • Authorization basics
  • Access control
  • Secure analytics best practices

Module 13: Monitoring & Troubleshooting

  • Query monitoring
  • Logs analysis
  • Debugging basics
  • Troubleshooting techniques

Module 14: PrestoDB with Programming Languages

  • Python integration basics
  • Java basics
  • JDBC connectivity
  • REST API basics

Module 15: Docker & Kubernetes Integration

  • PrestoDB in Docker
  • Containerized analytics setup
  • Kubernetes basics for PrestoDB

Module 16: Cloud Deployment

  • PrestoDB on AWS
  • Azure deployment basics
  • Google Cloud basics
  • Cloud-native analytics concepts

Module 17: Real-Time Project Scenarios

  • Banking analytics platform
  • E-commerce analytics dashboard
  • Telecom reporting platform
  • Healthcare analytics system
  • Enterprise reporting solution

Module 18: Best Practices & Coding Standards

  • Query optimization best practices
  • Efficient analytics architecture
  • Secure query management
  • Scalable distributed systems

Module 19: Certification & Enterprise Scenarios

  • Enterprise analytics case studies
  • Hands-on labs
  • Real-world Big Data scenarios
  • Distributed SQL architecture discussions

Module 20: Interview Preparation

  • PrestoDB interview questions
  • Distributed SQL discussions
  • Big Data analytics scenarios
  • Data lake discussions
  • Resume preparation

Β 

πŸ’Ό Career Opportunities

  • PrestoDB Developer
  • Data Engineer
  • Big Data Engineer
  • Data Analyst
  • Cloud Data Engineer
  • Analytics Engineer

βœ… Benefits of Learning PrestoDB

  • High-demand Big Data analytics skill
  • Excellent for distributed SQL querying
  • Strong data lake analytics expertise
  • Faster multi-source analytics capability
  • Strong cloud & enterprise opportunities
  • Excellent global job demand

🌟 Why Choose GTC Trainings?

  • Real-time project exposure
  • Expert trainers
  • Hands-on practical learning
  • Interview preparation
  • Placement assistance
  • Flexible online training

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Who Can Learn ?

  • Students
  • Freshers
  • Software Developers
  • Data Engineers
  • Big Data Engineers
  • Data Analysts
  • Database Administrators (DBA)
  • Cloud Engineers
  • IT Professionals
  • Basic SQL and database knowledge is helpful but not mandatory.