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
  2. Core Concepts

Vision and Goals

Lyftrondata's vision is to unleash the potential of Modern Data Hub and data federation technologies. Backed by BigData technology stack, to concurrently allow for high compatibility with existing technologies used for data access and analysis. And abstraction layer provided for all applications and data, helps to achieve flexibility for change, pervasive and consistent data access, and greatly reduced costs because of less need to create physically integrated data structures.

The end result is greater agility from, and freer access to, an organization’s data assets and promotion of self-service. Among other benefits, offer an opportunity for organizations to change and optimize the manner in which data is physically persisted, while not impacting the applications and business processes.

Lyftrondata's top goals are:

  • Through Modern Data Hub enable customers to rapidly develop and deploy data services that access, federate, abstract, and deliver data on-premise and in the cloud

  • Data efficiently delivered via established protocols and technologies can be reused on multiple projects, allowing to achieve agility

  • Gain faster business insights by almost instant, access to all the data, in a customizable and secure way

  • Respond faster to ever changing requirements of analytics and BI enabling 5-10 times shorter time to solution than traditional EDW

  • Enable savings of 50-75% over data replication and consolidation.

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Last updated 10 months ago