Tailer Documentation
  • What is Tailer Platform?
  • Getting Started
    • Prepare your local environment for Tailer
    • Install Tailer SDK
    • Set up Google Cloud Platform
    • Encrypt your credentials
  • [Tutorial] Create a first data pipeline
    • Introduction
    • Prepare the demonstration environment
    • Copy files from one bucket to another
    • Load files into BigQuery tables
    • Prepare data
    • Build predictions
    • Export data
    • Congratulations!
    • [Video] Automatic Script
      • SQL script file
      • DDL script file
      • Tables to Tables script file
      • Launch configuration and furthermore
  • Data Pipeline Operations
    • Overview
    • Set constants with Context
      • Context configuration file
    • Move files with Storage to Storage
      • Storage to Storage configuration file
    • Load data with Storage to Tables
      • Storage to Tables configuration file
      • Storage to Tables DDL files
    • Stream incoming data with API To Storage
      • API To Storage configuration file
      • API To Storage usage examples
    • Transform data with Tables to Tables
      • Tables to Tables configuration file
      • Table to Table SQL and DDL files
    • Export data with Tables to Storage
      • [V3] Table to Storage configuration file
      • Table to Storage SQL file
      • [V1-V2: deprecated] Table to Storage configuration file
    • Orchestrate processings with Workflow
      • [V2] Workflow configuration file
      • [V1: deprecated] Workflow configuration file
    • Convert XML to CSV
      • Convert XML to CSV configuration file
    • Use advanced features with VM Launcher
      • Process code with VM Launcher
        • VM Launcher configuration file for code processing
      • Encrypt/Decrypt data with VM Launcher
        • VM Launcher configuration file for data encryption
        • VM Launcher configuration file for data decryption
    • Monitoring and Alerting
      • Monitoring and alerting parameters
    • Asserting Data quality with Expectations
      • List of Expectations
    • Modify files with File Utilities
      • Encrypt/Decrypt data with File Utilities
        • Configuration file for data encryption
        • Configuration file for data decryption
    • Transfer data with GBQ to Firestore
      • Table to Storage: configuration file
      • Table to Storage: SQL file
      • VM Launcher: configuration file
      • File-to-firestore python file
  • Tailer Studio
    • Overview
    • Check data operations' details
    • Monitor data operations' status
    • Execute data operations
    • Reset Workflow data operations
    • Archive data operations
    • Add notes to data operations and runs
    • View your data catalog
    • Time your data with freshness
  • Tailer API
    • Overview
    • Getting started
    • API features
  • Release Notes
    • Tailer SDK Stable Releases
    • Tailer Beta Releases
      • Beta features
      • Beta configuration
      • Tailer SDK API
    • Tailer Status
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  • Introduction
  • What makes Tailer special?
  • Main features
  • Who is Tailer intended for?
  • Data engineers
  • Data scientists
  • Decision makers

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What is Tailer Platform?

Welcome to Tailer, an Open Source data platform dedicated to retailers.

NextPrepare your local environment for Tailer

Last updated 1 year ago

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Introduction

Retail companies need to handle ever-growing amounts of data. To do so, they require a simple, scalable and easy-to-implement solution offering instant performance at an affordable cost.

Tailer aims at helping all members of B2C companies that need to make sense of huge amounts of sales, inventory, operational, or customer data, to promote their data-driven transformation.

"Tailer" is an anagram of "Retail". As a high tech haute couture solution, it allows you to tailor your data, e-commerce, and sales predictions to your needs.

What makes Tailer special?

Easy to use, and quick to get up and running, Tailer allows you to achieve your business objectives faster.

As an Open Source solution, Tailer aims at gathering and federating a community of retail industry actors. Thanks to this, and the use of Google Cloud’s affordable resources, it has a particularly low TCO.

Easy to integrate, Tailer can be deployed in only 24h to 48h, and runs inside your own cloud environment.

Tailer is really agile, as its data flows adapt to all contexts. Being DevOps-ready, it allows you to adopt an iterative approach, and a Git branching strategy.

Main features

Tailer offers the following features:

  • Accessing and securing data

  • Gathering and organizing data

  • Transforming and enriching data

  • Using data for analysis and predictions

Data engineers

With Tailer, data engineers can take advantage of a data-centric, collaborative development environment to implement complex real-time big data workflows.

Data scientists

Data scientists can use Tailer to work directly within the company data lake without any technical restriction, and implement predictive models in one click.

Decision makers

Decision makers can take advantage of the better, quicker business insights achieved thanks to Tailer Platform to boost the data-driven transformation of their company.

Who is Tailer intended for?

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