DataOps Dataflow

A holistic component-based platform for automating Data Reconciliation tests in modern Data Lake and Cloud Data Migration projects using Apache Spark.

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Compare billions of records using the horizontally scalable clusters such as AWS EMR or Azure Databricks.

Key Features & Benefits

Automate the cloud data testing of all your ETL, Big Data, Data Warehouse, and Data Migration projects.

Built using Apache Spark

Dataflow is built using Apache Spark, a distributed data processing engine that can process large volumes of data in parallel and in-memory.

Data Migration Testing

Say NO to tedious, erratic tools and processes for Data Migration testing. Dataflow is your ideal solution, capable of automating Data Migration testing of any kind.

Data Observability

Data Flow continuously profiles the data being ingested and uses Machine Learning to detect anomalies in your latest data automatically.

Data Reconciliation

Compares data and finds differences between source and target data. Helps ensure that there are no discrepancies and reconciliation is done with absolute confidence.

Visual Test Case Builder

Has a unique visual test case builder with drag & drop capabilities and a query builder that enables defining tests without manually typing in queries.

Component-Based

Dataflow uses a component-based approach to ingest, process, validate, transform and synchronize your data. Build & run the Dataflow and see results in minutes.

All Data Sources

We support your data source in whichever form it is. You think of any kind of data source – whether it is a relational, NoSQL, Cloud, or Flat File data source – we support all.

On-Premise or Cloud

Data Flow is engineered to suit almost every kind of topology – be it on-premise (Standalone, Hadoop) or Cloud-based (AWS, Azure, Google) deployment.

Enterprise Collaboration

Capability to assemble and schedule test plans. Email notification, web reporting and JIRA integration enables sharing of test results.

Get the Power of DataOps DataFlow

DataOps Dataflow is a modern, web browser-based solution for automating the testing of ETL, Data Warehouse, and Data Migration projects. Use Dataflow to inject data from any of the varied data sources, compare data, and load differences to S3 or a database. With fast and easy to set up, create and run dataflow in minutes. A best in the class testing tool for Big Data Testing

DataOps Dataflow can integrate with all modern and advanced data sources including RDBMS, NoSQL, Cloud, and File-Based.

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Enables Continuous Integration

By automating the testing of Data Lake and Data Migration projects, DataOps DataFlow enables Continuous Integration.

Integrates with Jenkins: DataOps Dataflow provides a command-line interface for kicking of Dataflows and Pipelines. Customers have used this interface to execute tests automatically from Jenkins.
Email Notifications: Key stakeholders are automatically notified by email.
Web Reporting: DataOps DataFlow comes with out-of-the-box web reporting. Queries can be executed on the Dataflow repository for additional reporting.

Connects to all Popular Data Sources

We support your data source in whichever form it is. You think of any kind of data source – whether it is a relational, NoSQL, cloud, or file data source – we support most of them.

Data Transformation Testing

DataOps Dataflow supports testing of Data transformations by providing a visual test case builder that supports extracting test data from multiple sources in a single test case.

SQL Component: Support transforming data using Spark SQL queries.
Code Component: Supports Python, Scala and R
Attribute Component: Rename columns and use spark SQL UDFs to transform data

See DataOps DataFlow in action

Add value to your Big Data Analytics projects and save money.

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