Remove Data Governance Remove Data Validation Remove Data Workflow Remove Hadoop
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DataOps Tools: Key Capabilities & 5 Tools You Must Know About

Databand.ai

Poor data quality can lead to incorrect or misleading insights, which can have significant consequences for an organization. DataOps tools help ensure data quality by providing features like data profiling, data validation, and data cleansing.

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The DataOps Vendor Landscape, 2021

DataKitchen

We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . Airflow — An open-source platform to programmatically author, schedule, and monitor data pipelines.

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DataOps: What Is It, Core Principles, and Tools For Implementation

phData: Data Engineering

phData Cloud Foundation is dedicated to machine learning and data analytics, with prebuilt stacks for a range of analytical tools, including AWS EMR, Airflow, AWS Redshift, AWS DMS, Snowflake, Databricks, Cloudera Hadoop, and more. This proactive approach to data validation allows you to minimize risks and get ahead of the issue.

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