Best Data Lineage Tools for Google Cloud BigQuery

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

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

  • 1
    Immuta Reviews
    Immuta's Data Access Platform is built to give data teams secure yet streamlined access to data. Every organization is grappling with complex data policies as rules and regulations around that data are ever-changing and increasing in number. Immuta empowers data teams by automating the discovery and classification of new and existing data to speed time to value; orchestrating the enforcement of data policies through Policy-as-code (PaC), data masking, and Privacy Enhancing Technologies (PETs) so that any technical or business owner can manage and keep it secure; and monitoring/auditing user and policy activity/history and how data is accessed through automation to ensure provable compliance. Immuta integrates with all of the leading cloud data platforms, including Snowflake, Databricks, Starburst, Trino, Amazon Redshift, Google BigQuery, and Azure Synapse. Our platform is able to transparently secure data access without impacting performance. With Immuta, data teams are able to speed up data access by 100x, decrease the number of policies required by 75x, and achieve provable compliance goals.
  • 2
    Dataedo Reviews

    Dataedo

    Dataedo

    $49 per month
    Your metadata can be discovered, documented and managed. Dataedo has multiple automated metadata scanners. These scanners connect to different database technologies, extract data structures, and then load them into the metadata repository. In just a few clicks you can create a catalog of all your data and then describe each element. With business-friendly aliases, decrypt column and table names and provide meaning and purpose to data assets with descriptions and custom fields. To find out what data is stored in your data asset, you can use sample data. Make sure you have a better understanding of the data before you use it. Data profiling can help ensure high quality data. Data profiling allows everyone to have access to data knowledge. A lightweight, on-premises data catalogue can help you build data literacy, democratize data, and empower your employees to make better data use. A data catalog can help you increase data literacy.
  • 3
    Decube Reviews
    Decube is a comprehensive data management platform designed to help organizations manage their data observability, data catalog, and data governance needs. Our platform is designed to provide accurate, reliable, and timely data, enabling organizations to make better-informed decisions. Our data observability tools provide end-to-end visibility into data, making it easier for organizations to track data origin and flow across different systems and departments. With our real-time monitoring capabilities, organizations can detect data incidents quickly and reduce their impact on business operations. The data catalog component of our platform provides a centralized repository for all data assets, making it easier for organizations to manage and govern data usage and access. With our data classification tools, organizations can identify and manage sensitive data more effectively, ensuring compliance with data privacy regulations and policies. The data governance component of our platform provides robust access controls, enabling organizations to manage data access and usage effectively. Our tools also allow organizations to generate audit reports, track user activity, and demonstrate compliance with regulatory requirements.
  • 4
    Castor Reviews

    Castor

    Castor

    $699 per month
    Castor is a data catalogue that can be adopted by all employees. Get a complete overview of your data environment. Our powerful search engine makes it easy to find data quickly. Access data quickly and easily by joining a new data infrastructure. Expand beyond the traditional data catalog. Modern data teams have multiple data sources. Instead of building one truth, they build it. Castor's delightful and automated documentation makes it easy to trust data. In minutes, you can get a column-level view of your cross-system data lineage. To build trust in your data, get a bird's-eye view of your data pipelines. All you need to troubleshoot data issues, conduct impact analyses, and comply with GDPR is one tool. Optimize performance, cost compliance, security, and security for data. Our automated infrastructure monitoring system will keep your data stack healthy.
  • 5
    Weld Reviews

    Weld

    Weld

    €750 per month
    Your data models can be created, edited, and organized. You don't need another data tool to manage your data models. Weld allows you to create and manage them. It is packed with features that make it easy to create your data models: smart autocomplete, code folding and error highlighting, audit logs and version control, collaboration, and version control. We use the same text editor that VS Code - it is fast, powerful, and easy to read. Your queries are organized in a searchable and easily accessible library. Audit logs allow you to see when and by whom the query was last updated. Weld Model allows you to materialize models as views, tables, incremental tables, and views. You can also create custom materializations of your design. With the help of a dedicated team, you can manage all your data operations from one platform.
  • 6
    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.
  • 7
    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.
  • 8
    Select Star Reviews

    Select Star

    Select Star

    $270 per month
    In just 15 minutes, you can set up your automated data catalogue and receive column-level lines, Entity Relationship diagrams, and auto-populated documentation in 24 hours. You can easily tag, find, and add documentation to data so everyone can find the right one for them. Select Star automatically detects your column-level data lineage and displays it. Now you can trust the data by knowing where it came. Select Star automatically displays how your company uses data. This allows you to identify relevant data fields without having to ask anyone else. Select Star ensures that your data is protected with AICPA SOC2 Security, Confidentiality and Availability standards.
  • 9
    Metaplane Reviews

    Metaplane

    Metaplane

    $825 per month
    In 30 minutes, you can monitor your entire warehouse. Automated warehouse-to-BI lineage can identify downstream impacts. Trust can be lost in seconds and regained in months. With modern data-era observability, you can have peace of mind. It can be difficult to get the coverage you need with code-based tests. They take hours to create and maintain. Metaplane allows you to add hundreds of tests in minutes. Foundational tests (e.g. We support foundational tests (e.g. row counts, freshness and schema drift), more complicated tests (distribution shifts, nullness shiftings, enum modifications), custom SQL, as well as everything in between. Manual thresholds can take a while to set and quickly become outdated as your data changes. Our anomaly detection algorithms use historical metadata to detect outliers. To minimize alert fatigue, monitor what is important, while also taking into account seasonality, trends and feedback from your team. You can also override manual thresholds.
  • 10
    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.
  • 11
    Secoda Reviews

    Secoda

    Secoda

    $50 per user per month
    Secoda AI can help you generate documentation and queries from your metadata. This will save your team hundreds of hours of tedious work. Secoda AI will also generate documentation and queries based on your metadata. This will save your team hundreds of tedious hours and redundant data requests. Search across all columns, dashboards and metrics, as well as tables, dashboards and tables. AI-powered searches allow you to ask any question and receive a contextual response quickly. Answer questions. Our API allows you to integrate data discovery into your workflow, without disrupting the flow. Perform bulk updates, tag PII, manage tech debt and more. Eliminate manual errors and have complete trust in your knowledge base.
  • 12
    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.
  • 13
    Privacera Reviews
    Multi-cloud data security with a single pane of glass Industry's first SaaS access governance solution. Cloud is fragmented and data is scattered across different systems. Sensitive data is difficult to access and control due to limited visibility. Complex data onboarding hinders data scientist productivity. Data governance across services can be manual and fragmented. It can be time-consuming to securely move data to the cloud. Maximize visibility and assess the risk of sensitive data distributed across multiple cloud service providers. One system that enables you to manage multiple cloud services' data policies in a single place. Support RTBF, GDPR and other compliance requests across multiple cloud service providers. Securely move data to the cloud and enable Apache Ranger compliance policies. It is easier and quicker to transform sensitive data across multiple cloud databases and analytical platforms using one integrated system.
  • 14
    Secuvy AI Reviews
    Secuvy, a next-generation cloud platform, automates data security, privacy compliance, and governance via AI-driven workflows. Unstructured data is treated with the best data intelligence. Secuvy, a next-generation cloud platform that automates data security, privacy compliance, and governance via AI-driven workflows is called Secuvy. Unstructured data is treated with the best data intelligence. Automated data discovery, customizable subjects access requests, user validations and data maps & workflows to comply with privacy regulations such as the ccpa or gdpr. Data intelligence is used to locate sensitive and private information in multiple data stores, both in motion and at rest. Our mission is to assist organizations in protecting their brand, automating processes, and improving customer trust in a world that is rapidly changing. We want to reduce human effort, costs and errors in handling sensitive data.
  • 15
    Datakin Reviews

    Datakin

    Datakin

    $2 per month
    You can instantly see the order in your complex data world and know exactly where to find answers. Datakin automatically tracks data lineage and displays your entire data ecosystem as a rich visual graph. It clearly shows the upstream and downstream relationships of each dataset. The Duration tab summarizes the job's performance and its upstream dependencies in a Gantt-style graph. This makes it easy to identify bottlenecks. The Compare tab allows you to see how your jobs and data have changed over time. Sometimes jobs that run well can produce poor output. The Quality tab shows you the most important data quality metrics and how they change over time. This makes anomalies easily visible. Datakin allows you to quickly identify the root cause of problems and prevent them from happening again.
  • 16
    Foundational Reviews
    Identify code issues and optimize code in real-time. Prevent data incidents before deployment. Manage code changes that impact data from the operational database all the way to the dashboard. Data lineage is automated, allowing for analysis of every dependency, from the operational database to the reporting layer. Foundational automates the enforcement of data contracts by analyzing each repository, from upstream to downstream, directly from the source code. Use Foundational to identify and prevent code and data issues. Create controls and guardrails. Foundational can be configured in minutes without requiring any code changes.
  • 17
    AnalyticsCreator Reviews
    AnalyticsCreator lets you extend and adjust an existing DWH. It is easy to build a solid foundation. The reverse engineering method of AnalyticsCreator allows you to integrate code from an existing DWH app into AC. So, more layers/areas are included in the automation. This will support the change process more extensively. The extension of an manually developed DWH with an ETL/ELT can quickly consume resources and time. Our experience and studies found on the internet have shown that the longer the lifecycle the higher the cost. You can use AnalyticsCreator to design your data model and generate a multitier data warehouse for your Power BI analytical application. The business logic is mapped at one place in AnalyticsCreator.
  • 18
    Trifacta Reviews
    The fastest way to prepare data and build data pipelines in cloud. Trifacta offers visual and intelligent guidance to speed up data preparation to help you get to your insights faster. Poor data quality can cause problems in any analytics project. Trifacta helps you to understand your data and can help you quickly and accurately clean up it. All the power without any code. Trifacta offers visual and intelligent guidance to help you get to the right insights faster. Manual, repetitive data preparation processes don't scale. Trifacta makes it easy to build, deploy, and manage self-service data networks in minutes instead of months.
  • 19
    IBM Databand Reviews
    Monitor your data health, and monitor your pipeline performance. Get unified visibility for all pipelines that use cloud-native tools such as Apache Spark, Snowflake and BigQuery. A platform for Data Engineers that provides observability. Data engineering is becoming more complex as business stakeholders demand it. Databand can help you catch-up. More pipelines, more complexity. Data engineers are working with more complex infrastructure and pushing for faster release speeds. It is more difficult to understand why a process failed, why it is running late, and how changes impact the quality of data outputs. Data consumers are frustrated by inconsistent results, model performance, delays in data delivery, and other issues. A lack of transparency and trust in data delivery can lead to confusion about the exact source of the data. Pipeline logs, data quality metrics, and errors are all captured and stored in separate, isolated systems.
  • 20
    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.
  • 21
    Truedat Reviews

    Truedat

    Bluetab Solutions

    Bluetab Solutions developed Truedat, an open-source data governance business solution tool. It was created to help our clients become data-driven businesses. We assist in defining business processes, roles and responsibilities. We can also help you put these processes into action. Integration and customization of truedat’s open-source components to support data governance processes. We guarantee the maintenance and support of the solution modules we have installed. Based on our extensive experience, we have created a solution that addresses the need for Data Governance. This allows you to manage complex and changing data architectures. Truedat is becoming more important due to the increasing migration of enterprise IT platforms into cloud, multi-cloud, hybrid architectures. This increases the complexity, sources, and types of data. Our Data Governance consulting and development experience spans more than 8 years.
  • 22
    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.
  • 23
    Aggua Reviews
    Aggua is an AI platform with augmented data fabric that gives data and business teams access to their data. It creates Trust and provides practical Data Insights for a more holistic and data-centric decision making. With just a few clicks, you can find out what's happening under the hood of your data stack. You can access data lineage, cost insights and documentation without interrupting your data engineer's day. With automated lineage, data engineers and architects can spend less time manually tracing what data type changes will break in their data pipelines, tables, and infrastructure.
  • 24
    Validio Reviews
    Get a clear view of your data assets: popularity, usage, and schema coverage. Get important insights into your data assets, such as popularity and utilization. Find and filter data based on tags and descriptions in metadata. Get valuable insights about your data assets, such as popularity, usage, quality, and schema cover. Drive data governance and ownership throughout your organization. Stream-lake-warehouse lineage to facilitate data ownership and collaboration. Lineage maps are automatically generated at the field level to help understand the entire data ecosystem. Anomaly detection is based on your data and seasonality patterns. It uses automatic backfilling from historical data. Machine learning thresholds are trained for each data segment and not just metadata.
  • 25
    Datalogz Reviews
    Data knowledge management platform that allows teams to simplify data discovery and understanding with the ultimate goal to be able to trust their data. Stop costly mistakes and misreporting analytics today!
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