Data Observability For Data Scientists

Detect Data Quality issues in the data that you use for Machine Learning

Do you trust the data that you use for Data Science?

Detect Data Quality issues in source data and the data lake that would affect the performance of your ML model

Self-service Data Quality

Self-service Data Quality

Analyze the Data Quality of data sources for your ML models directly from your desk.

DQO.ai comes with Data Quality checks that will validate the most popular Data Quality issues that would make the data unusable for Machine Learning. Simply connect to your data source, enable required quality checks and verify your source data.

  • Built-in standard Data Quality checks
  • Run Data Quality checks directly from your desktop
  • Validate your data sources before you you start building an ML model

Training data revalidation

Training data revalidation

Automatically observe the quality of the data that is used for your ML model retraining. Never retrain your ML model using a low quality data.

DQO.ai is a Data Observability platform that continuously runs your Data Quality checks every day or when the source data is updated. Ensure that the quality of your data meets the requirements for your ML model.

  • Validate your training data every day
  • Detect outliers in your data sources that could severely impact the ML performance
  • Find inconsistencies in the data

Data Quality and ML in one place

Data Quality and ML in one place

Store the source code of your Data Quality rules and your Machine Learning scripts together in one place. Keep the Data Quality requirements aligned with your ML model.

DQO.ai Data Observability tool, designed by Data Science engineers for Data Science engineers. All data quality rules are stored in text files that you can store in Git along with your ML scripts. The Data Quality rules are editable with all popular editors (like VSCode) using autocomplete.

  • Store Data Quality rules in Git
  • Edit Data Quality rules with a text editor
  • Get auto suggestions (autocomplete) of Data Quality rules

Measure level of your data correctness in your database

Measure level of your data correctness in your database

Be familiar with data you store in your database, by having visualized results of data observability, quality test performed on your data.

DQO.ai is a Data Observability platform that continuously runs your Data Quality checks every day or when the source data is updated. Ensure that data you have in database is in good condition and you can rely on it.

  • Validate your data every day
  • Find inconsistencies in the data
  • Detect outliers in your data sources

No one can understand your data like we do!