OwlDQ User Guide
OwlDQ User Guide
OwlDQ
Release Notes
Our Approach
Our Story
What is OwlDQ
Get Started
Install
Start for free
Cloud Native Deployment
Cloud Native OwlDQ
Preparing for Cloud Native Deployment
Deploying Cloud Native OwlDQ
Cloud Hadoop Deployment
EMR
OwlCheck Examples
OwlCheck JDBC
OwlCheck Hive
OwlCheck Files
OwlCheck JSON
OwlCheck Kafka
OwlCheck MySql
Data Quality Pipelines
OwlCheck Spark
OwlCheck Databricks
OwlCheck Cron
OwlCheck S3
OwlCheck HDFS
OwlCheck MongoDB
OwlCheck Zeppelin
OwlCheck LinkId
OwlCheck Back Run
OwlCheck Validate Source
OwlCheck 43M rows
OwlCheck Transform
More...
How OwlDQ
Builds a Better DQ Dashboard
Ensures CCPA & GDPR
Makes your Data Lake better.
Speeds Migrations/Enables Replications
Assists Data Aggregation
Security
Owl Security
Scorecards
Dataset Scorecard
Group Scorecard
List View
Connecting to DBs in Owl Web
Owl DB Connection
Core Components
Overview
Profile
Behaviors
Schema Evolution
Outliers
Shapes
Validate Source
Rules
Duplicates
Explorer
Explorer 2
Pattern Mining
Missing Records
Labeling / Training
Item Labeling
Peak vs Off Peak
Graph
Process Dependency
Dataset Dependency
ARTICLES
Creating a Data Quality Pipeline
APIs
Swagger
Job Server
Custom Configurations
Notebook API
Catalog
Catalog
Catalog Bulk Actions
Cluster Health Report
Use-Cases
Bank Loans
Financial FxRate Data
Intraday Positions
Security Reference Data
Copying or Moving data
Cyber Anomalies in Real-Time
Owl Time
Owl Time Zone API
Alerts
Email Alerts
Troubleshooting
Cloudera CLASSPATH
Performance Tuning
Deploy Mode
Advanced
Add Date Column
Behavioral Dimension
Column Deltas
File Look Back
Filter & Filter Not
Multiple Pattern Relationships
Nulls in Datasets
Reference Checks
Transform Expressions
Prescriptive Personas
Multi-Tenant
Multi-Tenancy
Reports
Owl Summary Reports
Dataset Report
Coverage Report
Scheduler
Schedule Management
Schedule Owlchecks
View/Re-Run Scheduled Jobs
API-Core
Notebook/Spark
JWT
Cookie
DQ is the difference
Owl's Scorecard and 9 Dimensions of DQ
Best Practices
Healthcare Data Quality
Smart Meter Data
Health Insurance Claims Data
OBSERVATION ASSIGNMENTS
Assignment Queue(s)
Internal Assignment
External Assignment
Business Units
APIs
ERD
FAQ
Benchmarks
Performance Tests
Rules Import Export
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Column Deltas

Example

-ds dataset_deltas,
-rd "2019-07-15" \
-q "select * from nyse where run_dt = '2019-07-14'" \
-lib "/opt/owl/drivers/postgres/" \
-cxn postgres \
-record "SYMBOL"

A simple way to see if distinct values in a given column are being added or dropped compared to the previous run

-record "SYMBOL"

In this example, if a new symbol is added or dropped it will appear in the Records section of the hoot page.

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Behavioral Dimension
Next - Advanced
File Look Back
Last updated 2 years ago
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