Best Data Lineage Tools for Google Cloud Platform

Find and compare the best Data Lineage tools for Google Cloud Platform in 2024

Use the comparison tool below to compare the top Data Lineage tools for Google Cloud Platform on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

  • 1
    OvalEdge Reviews

    OvalEdge

    OvalEdge

    $1,300/month
    1 Rating
    OvalEdge, a cost-effective data catalogue, is designed to provide end-to-end data governance and privacy compliance. It also provides fast, reliable analytics. OvalEdge crawls the databases, BI platforms and data lakes of your organization to create an easy-to use, smart inventory. Analysts can quickly discover data and provide powerful insights using OvalEdge. OvalEdge's extensive functionality allows users to improve data access, data literacy and data quality.
  • 2
    Microsoft Purview Reviews
    Microsoft Purview is a unified data governance service that helps you manage and govern your on-premises, multicloud, and software-as-a-service (SaaS) data. You can easily create a comprehensive, up-to date map of your data landscape using automated data discovery, sensitive classification, and end to end data lineage. Data consumers can find trustworthy, valuable data. Automated data discovery, lineage identification and data classification across on and off-premises, multicloud, as well as SaaS sources. For more effective governance, a unified map of all your data assets and their relationships. Semantic search allows data discovery using technical or business terms. Get insight into the movement and location of sensitive data in your hybrid data landscape. Purview Data Map will help you establish the foundation for data usage and governance. Automate and manage metadata from mixed sources. Use built-in and customized classifiers to classify data and Microsoft Information Protection sensitive labels to protect it.
  • 3
    Ataccama ONE Reviews
    Ataccama is a revolutionary way to manage data and create enterprise value. Ataccama unifies Data Governance, Data Quality and Master Data Management into one AI-powered fabric that can be used in hybrid and cloud environments. This gives your business and data teams unprecedented speed and security while ensuring trust, security and governance of your data.
  • 4
    Y42 Reviews

    Y42

    Datos-Intelligence GmbH

    Y42 is the first fully managed Modern DataOps Cloud for production-ready data pipelines on top of Google BigQuery and Snowflake.
  • 5
    Masthead Reviews

    Masthead

    Masthead

    $899 per month
    View the impact of data issues in real time without running SQL. We analyze your logs to identify freshness anomalies and volume, schema changes, pipeline errors and their impact on your business. Masthead monitors each table, script, process and dashboard in your data warehouse, as well as the connected BI tools, for anomalies. It alerts data teams in real-time if data failures happen. Masthead shows data anomalies, pipeline errors and their implications on data consumers. Masthead maps lineage data issues, so you can troubleshoot in minutes, not hours. It was a game changer for us to get a comprehensive overview of all processes within GCP without having to give access our data. It saved us time and money. You can now see the cost of every pipeline in your cloud, irrespective of whether it is ETL. Masthead has AI-powered recommendations that can help you optimize your queries and models. Masthead can be connected to your data warehouse in 15 minutes.
  • 6
    Databricks Data Intelligence Platform Reviews
    The Databricks Data Intelligence Platform enables your entire organization to utilize data and AI. It is built on a lakehouse that provides an open, unified platform for all data and governance. It's powered by a Data Intelligence Engine, which understands the uniqueness in your data. Data and AI companies will win in every industry. Databricks can help you achieve your data and AI goals faster and easier. Databricks combines the benefits of a lakehouse with generative AI to power a Data Intelligence Engine which understands the unique semantics in your data. The Databricks Platform can then optimize performance and manage infrastructure according to the unique needs of your business. The Data Intelligence Engine speaks your organization's native language, making it easy to search for and discover new data. It is just like asking a colleague a question.
  • 7
    Axon Data Governance Reviews
    To support data-driven decision making, your teams need reliable data. Ensure they have it with automated, intelligent, and integrated data governance at scale. Axon Data Governance is the data marketplace and collaboration hub for successful, scalable data management programs. Facilitate knowledge transfer between communities and stakeholders to enable teams to learn from each other. With a carefully curated data marketplace, teams can quickly access, access, and understand data that is relevant to their analytics needs. Use governed data to support key initiatives, such as improving customer experience, and to deliver consistent, trusted results throughout your organization. To ensure compliance with regulations such as GDPR and CCPA, you should build governance and data privacy into your projects and processes from the beginning. To provide consistent business context across multiple tools, create a common data dictionary.
  • 8
    Tokern Reviews
    Open source data governance suite to manage data lakes and databases. Tokern is an easy-to-use toolkit for collecting, organizing and analysing metadata from data lakes. Runs as a command-line application for quick tasks. Run as a service to continuously collect metadata. Use reporting dashboards to analyze lineage, access control, and PII data. Or programmatically in Jupyter notebooks. Tokern is an open-source data governance suite for data lakes and databases. You can improve the ROI of your data, comply to regulations like HIPAA, CCPA, and GDPR, and protect your data from insider threats with confidence. Centralized metadata management for users, jobs, and datasets. Other data governance features are powered by this feature. Track column-level data lineage for Snowflake and AWS Redshift. You can build lineage using query history or ETL scripts. Interactive graphs and programming with APIs and SDKs allow you to explore lineage.
  • 9
    Talend Data Catalog Reviews
    Talend Data Catalog provides your organization with a single point of control for all your data. Data Catalog provides robust tools for search, discovery, and connectors that allow you to extract metadata from almost any data source. It makes it easy to manage your data pipelines, protect your data, and accelerate your ETL process. Data Catalog automatically crawls, profiles and links all your metadata. Data Catalog automatically documents up to 80% of the data associated with it. Smart relationships and machine learning keep the data current and up-to-date, ensuring that the user has the most recent data. Data governance can be made a team sport by providing a single point of control that allows you to collaborate to improve data accessibility and accuracy. With intelligent data lineage tracking and compliance tracking, you can support data privacy and regulatory compliance.
  • 10
    Sifflet Reviews
    Automate the automatic coverage of thousands of tables using ML-based anomaly detection. 50+ custom metrics are also available. Monitoring of metadata and data. Comprehensive mapping of all dependencies between assets from ingestion to reporting. Collaboration between data consumers and data engineers is enhanced and productivity is increased. Sifflet integrates seamlessly with your data sources and preferred tools. It can run on AWS and Google Cloud Platform as well as Microsoft Azure. Keep an eye on your data's health and notify the team if quality criteria are not being met. In a matter of seconds, you can set up the basic coverage of all your tables. You can set the frequency, criticality, and even custom notifications. Use ML-based rules for any anomaly in your data. There is no need to create a new configuration. Each rule is unique because it learns from historical data as well as user feedback. A library of 50+ templates can be used to complement the automated rules.
  • Previous
  • You're on page 1
  • Next