What is DataOps Environment Creation and Management?

With the DataKitchen Platform, create Kitchen workspaces in minutes – not weeks or months – to provide developers with a controlled and secure space to work. Kitchens contain pre-configured tools, datasets, hardware, and tests – everything users need to create and innovate. When new analytics are ready, Kitchens streamline an individual’s work into a team’s work and eventually into production by seamlessly merging to aligned environments.

What is DataOps Continuous Deployment?

Analytics can’t be agile with manual, error-prone, and time-consuming release processes. The DataKitchen Platform automates the end-to-end deployment process allowing analytics teams to test and release new analytics on-demand. Kitchens align and integrate toolchain environments so continuous deployment orchestrations can easily migrate analytics to production.

How to perform Automated Testing and Monitoring for DataOps?

Automated testing and monitoring is foundational to DataOps. The Platform enables you to dramatically improve data quality by catching costly and embarrassing data errors early. Embed automated tests at every step in your production and development pipelines. Use failures as an opportunity to add more tests and increase the reliability of your pipelines over time. Preset alerts to increase agility and reduce data downtime.

How Collaboration and Sharing works with DataOps?

DataOps is a team effort, and the DataKitchen Platform fosters collaboration by providing a common place to work and a single view of the end-to-end analytic process. Team members innovate and experiment in separate but aligned Kitchens, then integrate the collective work with confidence. Teams can easily save and share commonly used parts of pipelines as Ingredients – a significant productivity multiplier.

What is DataOps Process Analytics?

You can’t improve what you don’t measure. The DataKitchen Platform provides unprecedented visibility into the state of your data operations. Process metrics show how your teams are increasing collaboration, improving productivity, expanding test coverage, reducing errors, speeding deployment cycle times, and consistently meeting deadlines.

How to develop Modern, Secure, Scaleable Architecture for DataOps?

The DataKitchen Platform provides scalable and efficient end-to-end DataOps that adapts to your organization’s needs whether its on-prem, cloud, or hybrid infrastructure.

Open Source Data Observability and DataOps Software

Q: What is Tool-Agnostic DataOps?

Your teams already have the tools they need. With the DataKitchen DataOps Platform, virtually any analytic tool – from data access to value delivery – can be leveraged for successful DataOps. The Platform supports a vast array of native tooling integrations and flexible methods for integrating new tools as they come available.

Q: What is DataOps Meta-Orchestration?

Data organizations may be hierarchical and siloed, but analytics production cuts across teams, locations, and environments. The DataKitchen Platform meta-orchestrates all the steps in your production and development pipelines (and even pipelines of pipelines), providing a coherent framework for inter-team collaboration that transcends heterogeneous toolchains and distributed data centers.

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You can’t rapidly deliver trusted customer insight at the right time without our Data Observability and DataOps Software’s ability to identify problems in complex data systems and apply automation so problems never happen again.

Open Source Data Observability Software

Do you have way too many data and analytic tools? Can’t tell if they are working correctly?

DataOps Observability

Data breaks. Servers break. Your toolchain breaks. We ensure your team is the first to know and the first to solve with visibility across and down your data estate. We monitor every tool, server, software, and data set to ensure your customer trusts your data (and team!).

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Simple, Fast Data Quality Test Generation and Execution. Your data engineering starts with verifying that you can trust your data.

DataOps TestGen

Say goodbye to the complexity of writing data quality validation tests yourself. DataOps TestGen takes care of that for you, automating the terms and conditions of your data contract through simple, automatically generated data test creation, execution, and profiling.

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Open Source Data Observability

For Individuals

Free/Forever

Complete DataOps TestGen Product
One TestGen User
One TestGen Database Connection
One TestGen Project
TestGen Major Cloud Database Support
Complete DataOps Observability Product
One Observability User
One Observability Project
Open Source Observability Agents
Technical Features
Kubernetes/Docker Environment
No Single Sign-On
Community Releases
Community Support
Apache 2.0 License
Containerized Supporting Databases

Enterprise Data Observability

For Teams and Enterprises

USD$1,000/Month(Starting)

Complete DataOps TestGen Product
Unlimited TestGen Users
Unlimited TestGen Database Connections
Unlimited TestGen Projects
TestGen Major and Proprietary Database Support
Complete DataOps Observability Product
Unlimited Observability Users
Unlimited Observability Projects
Opens Source & DataKitchen Supported Observability Agents
Technical Features
Kubernetes/Docker Environment
Single Sign-On Support
Latest Releases
DataKitchen Support
DataKitchen Subscription License
Native Database Services

Cloud Data Observability

For Teams and Enterprises

USD$1,000/Month(Starting)

Complete DataOps TestGen Product
Unlimited TestGen Users
Unlimited TestGen Database Connections
Unlimited TestGen Projects
TestGen Major and Proprietary Database Support
Complete DataOps Observability Product
Unlimited Observability Users
Unlimited Observability Projects
Opens Source & DataKitchen Supported Observability Agents
Technical Features
Observability (Cloud), TestGen (On-Prem) Envroinment
Single Sign On Support
Latest Releases
DataKitchen Support
DataKitchen Subscription License
Native Database Services
Analytic Reports

Key Data Observability Use Cases

Data Analytics Use Case	When Does it Happen	Data Observability Challenge	Key Data Observability Product Feature	Key Benefit
Patch (or pushback): New data analysis and cleansing	Before New Data Sources Are Added To Production	Evaluate new data, find data hygiene issues, and communicate with your data providers.	DataOps TestGen’s data profiling of 51 data characteristics, then 27 data hygiene detector suggestions; UI to review and disposition	Save time, lower errors, improve data quality
Poll: Updates to existing data sources; Data ingestion monitoring	Continually	Find anomalies in data updates and notify the proper party in the right place.	DataOps TestGen’s auto-generation of data anomaly tests: freshness, schema, volume, and data drift checks. DataOps Observability Data Journeys, overview UI, and notification rules and limits	Find problem data quickly, save time, lower errors
Production: Monitoring of multi-tool, multi-data sets, multi-hop, data analytic production processes.	During The Production Cycle	Find data, SLA, and toolchain problems, local quickly, and notify quickly.	DataOps TestGen’s auto-generation of 32 data quality validation tests based on data profiling. 2 custom test types. Fast in database SQL execution (no data copies). DataOps Observability’s end-to-end Data Journeys are digital twins that represent your entire process and allow you to find, alert, and fix quickly.	Stop embarrassing customer errors, gain customer data trust, lower errors, improve team productvity
Push: Development Unit, Regression Tests, and Impact Assessment.	During The Development Process	Find problems in data or tools in development to validate code/configuration changes.	The combination of DataOps Observability and DataOps TestGen can be run in your development environment against test data to provide functional, unit, and regression tests.	Improve the speed and lower the risk of changes to production, less wasted time, improve productivity.
Parallel: Checking data accuracy during Data Migration projects: “Does It Match’?	During a Data Migration Process	Checking two data similar data sets or processes so they produce the same results.	DataOps TestGen can find errors between migrated data sets by comparing source and target data quality tests. DataOps Observability can monitor legacy tools and migrated cloud tools at the same time.	Lower risk of data errors and improve project delivery time.

DataOps Automation Software

Day 1 is building your data solution. Day 2 focuses on reducing production errors. Day 3 is reducing the time and risk of new changes. Focus on Day 3.

DataOps Automation

DataOps Automation meta-orchestrates all the steps in your production and development pipelines, providing a coherent framework for inter-team collaboration that transcends heterogeneous toolchains and distributed data centers. Permanently fix the cause of errors and bottlenecks by automating all your chosen technologies’ testing, deployment, and orchestration.

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DataKitchen Works With Your Existing Data & Analytic Toolchain

Your teams already have the tools they need (and love!). With the DataKitchen DataOps Observability and Automation Software, virtually any analytic tool – from data access to value delivery – can be leveraged for successful DataOps. The Software supports a vast array of native tooling integrations and flexible methods for integrating new tools as they come available.