Lyftrondata
  • Introduction
    • About Lyftrondata
    • Lyftrondata Feature
    • Lyftrondata System Architecture
      • Lyftrondata Integration Framework
      • Lyftrondata Connector Framework
    • Core Concepts
      • Data Pipelines
      • Vision and Goals
      • Sources and Destinations
        • Types of Sources
        • Types of Destination
    • Free Trial
    • Lyftrondata Apps
      • Data Loader
        • Full Load
        • Incremental Load
      • Data Mirror
        • Prerequisite
        • Integration
      • Data Vault
      • ELT
      • ETL
      • Data Analytics
    • Faq
  • Lyftrondata Connectors
    • Source
      • 📶Sales Analytics
      • 👨‍💻Technology Analytics
      • 💸Finance Analytics
      • 📊Business Analytics
      • 🤝Marketing Analytics
      • 🇸🇴Commerce Analytics
      • ☁️Weather Analytics
      • 🔃Supply Chain Analytics
      • ⏳Human Resources Analytics
    • Destinations
  • Managing Lyftrondata
    • Lyftrondata Installation
      • Requirements
      • On AWS Deployment
      • On AWS Deployment Using AMI
      • On Azure Deployment
      • On DigitalOcean Deployment
      • Deployment Info
    • Configure Lyftrondata
      • AWS S3/IAM User
      • Wasabi
      • Settings and Security
  • Developer Guides
    • Understand Lyftrondata
      • Lyftrondata Architecture
      • Libraries and Dependencies Used in Our Application
      • Services used by Lyftrondata
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  1. Introduction

Lyftrondata Apps

App Name
Description

Data Loader

Enables loading of data from various sources

Data Mirror

Enables real-time data replication and mirroring

Data Vault

Manages and secures historical data for long-term storage

Data Analytic

Provides tools for data analysis and insights

ETL

Facilitates Extract, Transform, and Load processes

ELT

Allows Extract, Load, and Transform operations

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Last updated 11 months ago