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User Guide
Introduction

Type to start searching
GitHub
 * Home
 * Introduction
 * Getting Started
 * API reference
 * Release Notes

User Guide
GitHub
 * Home
 * Introduction Introduction
   Table of contents
    * Managing Data Quality
    * Key Features
    * Seamless Integration and Deployment
    * Demo
    * Embarking on Your Journey

 * Getting Started
   Getting Started
    * Quick Start Guide
    * Technical Quick Start Guide
    * Glossary
    * Add Datastores
      Add Datastores
       * Datastores Overview
       * JDBC Datastores
         JDBC Datastores
          * BigQuery
          * Databricks
          * DB2
          * Hive
          * MariaDB
          * Microsoft SQL Server
          * MySQL
          * Oracle
          * PostgreSQL
          * Presto
          * Redshift
          * Snowflake
          * Synapse
          * Timescale DB
          * Trino
      
       * DFS Datastores
         DFS Datastores
          * DFS Datastore Overview
          * Amazon S3
          * Azure Blob Storage
          * Azure Datalake Storage
          * Google Cloud Storage
          * Qualytics File System (QFS)
      
       * Connections Overview
   
    * Datastore Operations
      Datastore Operations
       * Catalog
       * Profile
       * Scan
       * External Scan
   
    * Enrichment Datastores
      Enrichment Datastores
       * Overview
       * Data Preview
       * Add Enrichment
       * Link Enrichment
   
    * Containers
      Containers
       * Overview
       * Data Preview
       * Computed Tables and Files
       * Computed Fields
       * Export Metadata
       * Settings
         Settings
          * Identifiers
          * Grouping
          * General
   
    * Data Quality Checks
      Data Quality Checks
       * Overview
       * Check Templates
       * Authored
       * Inferred
       * Rule Types
         Rule Types
          * After Date
          * Aggregation Comparison
          * Any Not Null
          * Before Date Time
          * Between
          * Between Times
          * Contains Credit Card
          * Contains Email
          * Contains Social Security Number
          * Contains Url
          * Distinct Count
          * Entity Resolution
          * Equal to
          * Equal to Field
          * Exists In
          * Expected Schema
          * Expected Values
          * Field Count
          * Greater Than
          * Greater Than Field
          * Is Address
          * Is Credit Card
          * Is Replica Of
          * Is Type
          * Less Than
          * Less Than Field
          * Matches Pattern
          * Max Length
          * Max Partition Size
          * Max Value
          * Metric
          * Min Length
          * Min Partition Size
          * Min Value
          * Not Exists In
          * Not Future
          * Not Negative
          * Not Null
          * Positive
          * Predicted By
          * Required Values
          * Satisfies Expression
          * Sum
          * Time Distribution Size
          * Unique
          * User Defined Function
   
    * Anomalies
      Anomalies
       * Overview
       * Analysis
   
    * Explore
      Explore
       * Overview
       * Insights
       * Activity
       * Profiles
       * Checks
       * Anomalies
   
    * Freshness
      Freshness
       * Overview
   
    * Settings
      Settings
       * Tags
       * Notifications
         Notifications
          * Overview
          * Channels
            Channels
             * Email
             * HTTP Action
             * Microsoft Teams
             * PagerDuty
             * Slack
             * Webhook
      
       * Connections
       * Integrations
       * Security
       * Tokens
       * Health
   
    * Qualytics CLI
      Qualytics CLI
       * Overview
   
    * FAQ
      FAQ
       * Quality Scores
       * Printing This Guide
   
    * Misc
      Misc
       * SSO (Single Sign-On)
       * Deployment options
       * Installing helm for Qualytics single-tenant instance
       * Qualytics Scheduled Operations
       * DFS multi-token filename globbing

 * API reference
 * Release Notes

Table of contents
 * Managing Data Quality
 * Key Features
 * Seamless Integration and Deployment
 * Demo
 * Embarking on Your Journey


USER GUIDE: INTRODUCTION TO QUALYTICS

Qualytics is the Active Data Quality Platform that enables teams to manage data
quality at scale through advanced automation. Qualytics analyzes your historic
data for its shapes and patterns in order to infer contextual data quality rules
that are then asserted against new data (often in incremental loads) to identify
anomalies. When an anomaly is identified, Qualytics provides your team with
everything needed to take corrective actions using their existing data tooling &
preferred monitoring solutions.


MANAGING DATA QUALITY

With Qualytics, your data teams can quickly address data issues in a proactive
way by automating the discovery and maintenance of data quality measures you
need.

Here's how it works:

 1. Analyzing Historical Data: Qualytics examines your historical data to
    understand its patterns and characteristics, allowing it to create rules
    that define good data quality.

 2. Finding Anomalies: These rules, combined with any rules you create yourself,
    are used to identify any abnormalities or inconsistencies in your historical
    data or new data (even when new data is added incrementally).

 3. Taking Corrective Actions: When an anomaly is detected, Qualytics helps your
    team take appropriate actions. Utilizing tags, it can send notifications
    through the platforms you use (such as Teams, Slack, or PagerDuty), trigger
    workflows in tools (like Airflow, Fivetran or Airbyte), provide additional
    information about the anomaly to your chosen datastore (compatible with
    SQL-based integrations like dbt), and even suggest the best course of action
    through its user interface and API.

 4. Continuous Monitoring and Improvement: Qualytics continuously monitors and
    scores your data quality. It keeps your quality checks up to date, taking
    into account any changes in your actual data and your business needs. This
    ongoing process helps improve your overall data quality and boosts trust and
    confidence in your organization's data.

By leveraging Qualytics, you can efficiently manage data quality, proactively
address issues, and enhance trust in the data driving your organization.


KEY FEATURES

Qualytics offers a range of powerful features designed to enhance your data
quality management:

 1. Automated Data Profiling: Qualytics leverages your existing data to
    automatically generate profiles for each of your data assets. These profiles
    provide valuable insights into your data and serve as the foundation for
    maintaining data quality.

 2. Rule Inference: Crafting and maintaining data quality rules at scale can be
    a daunting task. Qualytics simplifies this process by automatically
    inferring appropriate data quality rules based on your data profiles. This
    saves you time and effort while ensuring accurate anomaly detection.

 3. Anomaly Detection: Identifying anomalies within your data is crucial for
    maintaining data quality. Qualytics excels in detecting anomalies at rest
    and in flight throughout your data ecosystem. By highlighting outliers and
    irregularities, it helps you identify and address data quality issues
    effectively.

 4. Anomaly Remediation: Once anomalies are detected, Qualytics provides the
    necessary tools to take corrective actions. It enables you to seamlessly
    integrate with your preferred data tooling and initiate remediation
    workflows. This ensures that data outliers are addressed promptly and
    efficiently.

 5. Freshness Monitoring: Qualytics includes functionality for monitoring data
    freshness Service Level Agreements (SLAs). It allows you to define and track
    SLAs for the timeliness of data updates, ensuring that your data remains
    up-to-date and meets the required service level agreements.

 6. Insights Dashboard: Qualytics provides an intuitive executive dashboard
    called Insights. This dashboard gives you a holistic view of the health and
    quality of your data. You can easily visualize key data quality metrics,
    track progress, and gain actionable insights. With the executive dashboard,
    you can make informed decisions and drive data-driven strategies for your
    organization.


SEAMLESS INTEGRATION AND DEPLOYMENT

Qualytics offers flexible integration options to fit your data infrastructure
seamlessly:

 * Deployment Options: Whether you prefer an on-premise, single-tenant cloud, or
   SaaS deployment, Qualytics adapts to your specific needs. It meets you where
   your data resides, ensuring a hassle-free integration process.

 * Support for Modern & Legacy Data Stacks: Qualytics seamlessly integrates with
   a wide range of data platforms. From modern solutions like Snowflake and
   Amazon S3 to legacy systems like Oracle and MSSQL, Qualytics supports your
   data stack. This versatility ensures that data quality remains a priority
   across all your data sources.


DEMO

Here is a short video demonstrating the platform with a quick walkthrough:


EMBARKING ON YOUR JOURNEY

This user guide will walk you through the key functionalities of Qualytics and
provide step-by-step instructions to help you make the most of this powerful
platform. Whether you are new to Qualytics or looking to deepen your
understanding, this guide will be your companion in optimizing your data quality
management.

Let's embark on this journey to empower your organization with accurate,
reliable, and trustworthy data using Qualytics!

--------------------------------------------------------------------------------

Last update: July 22, 2024
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