Data Observability v2 by Metaplane - Detailed Review
Data Tools
Data Observability v2 by Metaplane - Product Overview
Introduction to Metaplane’s Data Observability Platform
Metaplane’s Data Observability platform is an all-in-one solution aimed at preventing, detecting, and resolving data quality issues across an entire data stack. This platform is particularly useful for data-driven organizations seeking to ensure their data is accurate, reliable, and trustworthy.
Primary Function
The primary function of Metaplane is to provide comprehensive visibility and monitoring of the data pipeline. It uses machine learning-based anomaly detection to alert users to any issues across the data stack, from raw data to modeled data. This includes identifying upstream data quality issues, tracking schema changes, and detecting abnormal job runtimes for recurring jobs.
Target Audience
The target audience for Metaplane includes a wide range of stakeholders who rely on data to perform their jobs. This includes data consumers such as sales personnel, customer service, and business end users. Additionally, it benefits networking professionals, IT teams, administrators, and upper-level executives who base strategic decisions on reliable and fresh data.
Key Features
Automated Anomaly Detection
Metaplane employs ML-based, always-on monitoring to alert users to every issue across the data stack. It adapts to the specific patterns of each table and data point, considering seasonal and contextual variations.
100% Visibility into Data Pipelines
The platform provides complete visibility into critical objects, schema changes, and compute-heavy queries. This helps in identifying and optimizing cost and performance issues.
Column-Level Lineage
Metaplane offers column-level lineage for the entire data stack, which accelerates root cause analyses and helps in understanding the downstream impact of data changes.
Forecast Downstream Changes
Users can see all downstream changes before committing updates, such as dbt pull requests, to prevent breaking BI dashboards or other business applications.
Configurable Alerts
The platform allows for adjusting alert sensitivity and types, ensuring that users receive relevant alerts through their preferred communication tools.
Quick Setup and Minimal Maintenance
Metaplane can be integrated with modern, future, or historic data stacks in just a few clicks, with a setup time of as little as 30 minutes and no ongoing maintenance required.
Compliance and Security
Metaplane complies with major privacy standards such as GDPR, CCPA, and is HIPAA compliant, ensuring data security and regulatory adherence.
By offering these features, Metaplane helps data teams move faster, more confidently, and with greater trust from stakeholders, making it an essential tool for any data-driven organization.
Data Observability v2 by Metaplane - User Interface and Experience
User Interface of Metaplane’s Data Observability v2
The user interface is designed with a focus on clarity, ease of use, and enhanced visibility into your data.
Redesigned Monitor Page
The new monitor page has undergone a significant overhaul, featuring a more intuitive and visually appealing design. The top of the page now includes a redesigned graph that replaces the traditional y-axis with contextual axes. This change makes it easier to see the relationship between historical data and the most recent data points. You can now view the exact values for Metaplane’s predicted range and where the observed value falls within that range, eliminating the need for mental calculations.
Streamlined Workflows and Context
Below the graph, there is a table that provides additional context. This table shows whether an observed data point was within the expected range and, if not, whether it was higher or lower than expected. Manual thresholds are also displayed more clearly, making it easier to understand historical data behavior. An “Overview” section at the top right of the page offers high-level information about the monitor, including its current status and the last run time.
Configuration Options
The configuration options have been streamlined, with an explicit choice to switch between automatic, ML model-based monitoring and manual, threshold-based monitoring. There is also a new option to select a specific date to begin incorporating historical data into the model, which is useful if your data has changed significantly at a certain point. These options are easily accessible through a side menu.
Predictable Alerting Behavior
The alerting system has been simplified to ensure that the expected range on the graph and the range that triggers an alert are the same. This means that if a value falls outside the green area on the graph, an alert is sent. This change makes alert behavior more predictable and reduces the noise from unnecessary alerts.
Visibility for Snowflake Users
For users with Snowflake warehouses, Metaplane now captures snapshots of the freshness and row count of every table or view in the database. While this does not trigger alerts, it provides valuable historical metadata that can be accessed if issues arise. This feature allows for quick monitoring setup without the usual 3-5 day training period, as Metaplane already has the necessary historical data.
Ease of Use
The interface is designed to be user-friendly, making it easier for both data engineers and non-technical team members to engage with and understand the data. The UI is polished, ensuring that key information is easily visible and accessible. This includes clear indicators of when data points were marked as normal and when the monitor was last run, reducing the time and effort needed to interpret the data.
Overall User Experience
The overall user experience is enhanced by the integration of various features that reduce noise and streamline workflows. The new design and added context make it simpler to identify issues quickly and take corrective actions. The proactive approach to monitoring, combined with the ability to link data to business metrics, ensures that teams can focus on resolving issues that have the greatest impact on the business.
Data Observability v2 by Metaplane - Key Features and Functionality
Data Observability v2 by Metaplane
Data Observability v2 by Metaplane is a sophisticated platform that integrates AI and several key features to enhance data quality and observability. Here are the main features and how they work:
Redesigned Monitor Page
The new monitoring platform includes a completely redesigned monitor page. This redesign features a new graph at the top of the page with contextual axes, making it easier to see the relationship between historical data and the most recent data points. This visual improvement helps users quickly identify where the observed value falls within the predicted range without needing to perform mental calculations.
Predictable Alerting Behavior
The platform has streamlined alerting behavior, ensuring that the expected range on the graph and the range that triggers an alert are the same. This simplification eliminates the confusion between the displayed “normal” range and the alert-triggering range, making alerts more predictable and reliable. The system also removed the “Alert level” option, with plans to introduce a new method for fine-tuning the expected range in the future.
Greater Visibility into Underlying Data
For Snowflake users, Metaplane captures snapshots of the freshness and row count of every table or view in the database. While this does not trigger alerts, it provides historical metadata that can be useful for investigating issues. This feature allows users to quickly set up monitoring for tables without the usual 3-5 day training period, as Metaplane already has the necessary historical data.
Automated Anomaly Detection
The platform uses machine learning (ML) for automated anomaly detection. This ML-based monitoring alerts users to issues across their entire data stack, ensuring that any deviations from normal behavior are quickly identified and addressed.
Streamlined Configuration Options
Users can switch between automatic, ML model-based monitoring and manual, threshold-based monitoring. There is also an option to select a specific date to begin incorporating historical data into the model, which is useful if the data has materially changed over time.
Overview Section and Contextual Data
The monitor page includes a new “Overview” section that provides high-level information about the monitor, such as its current status and the last run time. The table below the graph offers additional context, showing whether observed data points are within the expected range and whether they are higher or lower than expected. This makes it easier to understand historical data behavior.
Column-Level Lineage and Forecasting
Metaplane provides column-level lineage for the entire data stack, which accelerates root cause analysis and helps users understand the downstream impact of changes. Additionally, the platform forecasts downstream changes for model updates, allowing users to see the effects before committing changes.
Tracking Warehouse Table Volume and Freshness
The platform automatically tracks the volume and freshness of warehouse tables, providing insights into warehouse spend. This feature is particularly useful for ensuring data trust and identifying potential issues with outdated or unmonitored data.
AI Integration
AI is integrated throughout the platform, particularly in anomaly detection and predictive analytics. The ML models help in setting dynamic baselines and identifying deviations from normal behavior, enabling proactive issue resolution. This integration ensures that the system can predict and prevent potential disruptions, reducing downtime and enhancing overall system reliability.
These features collectively enhance the visibility, predictability, and efficiency of data monitoring, making it easier for data engineers, analysts, and enterprise leaders to maintain high-quality data and make informed decisions.
Data Observability v2 by Metaplane - Performance and Accuracy
Performance
Metaplane is designed to provide real-time monitoring and alerts, which is crucial for timely intervention in data quality issues. Here are some performance highlights:Real-time Monitoring
Metaplane offers real-time monitoring capabilities, enabling organizations to receive immediate alerts and notifications when anomalies or issues are detected. This allows for prompt action to be taken, ensuring minimal disruption to data operations.Scalability
While Metaplane performs well, larger organizations with hundreds or thousands of tables may need to be cautious about alert fatigue. It is recommended to be rigorous about what alerts count as incidents to avoid overwhelming the system.Ease of Setup
Metaplane boasts a 30-minute setup process with no maintenance required, which is a significant advantage in terms of getting started quickly and efficiently.Accuracy
The accuracy of Metaplane’s data observability is supported by several features:Automated Anomaly Detection
Metaplane uses ML-based monitoring to detect issues across the entire data stack, including freshness and row count monitors. This helps in identifying data quality issues proactively.Data Lineage
The platform provides column-level lineage tracking, which helps in understanding the origin, transformations, and flow of the data. This is essential for accurate root cause analysis and troubleshooting.Configurable Alerts
Users can adjust alert sensitivity and types to ensure they receive relevant and accurate notifications, reducing the noise and focusing on critical issues.Limitations and Areas for Improvement
While Metaplane offers a comprehensive set of features, there are some limitations to consider:Feature Limitations
Compared to open-source alternatives like Great Expectations, Metaplane might not be as feature-rich or customizable. This could be a drawback for organizations with specific or advanced requirements.Cost
Metaplane is a commercial tool with a subscription-based pricing model, which may not be suitable for all organizations, especially those with budget constraints.Community Support
The community support for Metaplane is relatively smaller compared to open-source tools, which could impact the availability of community-driven solutions and support.Best Practices for Implementation
To maximize the performance and accuracy of Metaplane, it is important to avoid common mistakes such as:Over-monitoring
Avoid monitoring every single type of anomaly on every table, as this can lead to alert fatigue. Instead, be stringent about what alerts are set up and regularly re-evaluate monitor placements.Proactive Data Management
Ensure that data observability is integrated into broader data management practices, including incident management and response processes, to fully leverage the insights provided by the platform. By considering these aspects, organizations can effectively utilize Metaplane’s Data Observability platform to ensure high data quality and reliability. Data Observability v2 by Metaplane - Pricing and Plans
Pricing Range
The pricing for Metaplane varies widely. According to Vendr’s internal transaction data, the minimum price is around $3,000, and the maximum price is approximately $55,000 per year. The average annual cost is about $20,000.Plans and Features
While the specific tiers and their corresponding features are not explicitly detailed in the sources, here are some general features and aspects that can be associated with Metaplane’s offerings:General Features
- Automated Anomaly Detection: ML-based, always-on monitoring that alerts users to issues across the data stack.
- 100% Visibility: Into data pipelines, including critical objects, schema changes, and compute-heavy queries.
- Column-Level Lineage: To accelerate root cause analyses and understand downstream impact.
- Configurable Alerts: Adjust alert sensitivity and types sent to your communication tool of choice.
- Forecast Downstream Changes: See all downstream changes before committing model updates.
Setup and Maintenance
- 30-Minute Setup: No maintenance required; integrate with your data stack in a few clicks.
Free Options
Metaplane offers a free plan, which is unique among data observability platforms. This free plan allows users to get completely set up by themselves in minutes.Snowflake Integration
For Snowflake users, Metaplane has a native application available through the Snowflake Marketplace. During the public preview, this application is free, but once it is generally available, users will have to pay for it after a 30-day free trial. However, the specific pricing structure for this integration has not yet been determined. Given the current information, it is clear that Metaplane offers a range of features and a free plan, but the detailed tiered pricing structure and specific features per tier are not explicitly outlined in the available sources. For the most accurate and up-to-date pricing details, it would be best to contact Metaplane directly or check their official website. Data Observability v2 by Metaplane - Integration and Compatibility
Integration and Compatibility of Metaplane
Integration with Snowflake
Metaplane has a strong and integrated relationship with Snowflake, a cloud-based data warehousing platform. Metaplane offers more Snowflake integrations than any other data observability platform, supporting core data engineering features such as Tasks, Streams, Secure Data Shares, and Snowpipes. It also integrates with data app development features like Snowpark and Native Apps through Event Tables. The native application for Snowflake, available through the Snowflake Marketplace, allows joint customers to monitor and secure their data directly within the Snowflake environment. This integration eliminates the need to move data out of Snowflake, reducing costs and the risk of data exposure.Machine Learning and Automated Observability
Metaplane uses machine learning-based data quality monitoring to ensure data accuracy and trustworthiness. This automated observability extends from data ingestion through analysis, freeing data teams to focus on other initiatives rather than manually checking data pipelines.Compatibility and Scalability
Metaplane is designed to be highly scalable and can handle a wide range of data workloads. It integrates well with various data tools and platforms, although the current focus is heavily on Snowflake. There are plans to add integrations with more databases and other data sources in the future.User-Friendly and Broad Accessibility
Metaplane aims to make data observability accessible to a wider team beyond just data engineers. It provides a user-friendly interface and alerts teams to data anomalies, allowing them to diagnose downstream impacts and analyze upstream root causes. This makes it easier for non-technical stakeholders to engage with and understand data health.Security and Compliance
The integration within the Snowflake environment ensures that data is observed without the need for export, which is particularly beneficial for enterprises in highly regulated industries that need to meet compliance standards. This approach enhances security and compliance while ensuring data quality and performance.Conclusion
In summary, Metaplane’s strong integration with Snowflake and its use of machine learning for automated data observability make it a powerful tool for ensuring data quality and trustworthiness. While it is currently focused on Snowflake, there are plans to expand its compatibility with other data platforms and sources. Data Observability v2 by Metaplane - Customer Support and Resources
Customer Support
While the provided sources do not detail specific customer support channels such as phone numbers, email addresses, or live chat options, it is common for such platforms to offer multiple avenues for support. Typically, users can expect to find support through the platform’s website, possibly including a contact form, FAQ section, or a support portal where they can submit tickets.
Documentation and Guides
Metaplane provides comprehensive documentation and guides to help users get started and make the most out of the platform. For instance, the “Essential Data Observability Handbook” is available for download, which covers key concepts, benefits, and implementation strategies for data observability.
Community and Resources
Users can access various resources such as blog posts, case studies, and event recordings. For example, Metaplane offers articles like “6 Signs You Need a Data Observability Tool” and “The Data Leader’s Guide to Increasing Usage,” which provide valuable insights and best practices.
Integration and Setup Support
The platform is designed for easy integration, with features like a 30-minute setup process and no maintenance requirements. This suggests that users can quickly get started, and any issues during setup can likely be addressed through the available documentation or support channels.
Community Engagement
Metaplane also engages with its users through events and webinars, where they discuss topics related to data observability and share experiences from other users. This can be a valuable resource for learning from peers and industry experts.
Conclusion
In summary, while specific customer support channels are not detailed in the provided sources, Metaplane offers a range of resources including comprehensive documentation, guides, community engagement, and easy setup processes to support its users effectively.
Data Observability v2 by Metaplane - Pros and Cons
Advantages of Metaplane’s Data Observability v2
Metaplane’s Data Observability v2 offers several significant advantages that enhance data quality and reliability:Redesigned Monitor Page
The new monitor page features a more intuitive UI, including a redesigned graph that uses contextual axes to make historical and recent data points clearer. This allows users to see the exact values for Metaplane’s predicted range and where the observed value falls without needing additional calculations.Predictable Alerting Behavior
The system now ensures that the expected range on the graph and the range that triggers an alert are the same, making alert behavior more predictable. This simplification eliminates the need for the “Alert level” option, though a new method for fine-tuning the expected range is planned.Enhanced Visibility and Context
The monitor page includes an “Overview” section that provides high-level information about the monitor, such as its current status and last run time. The table below the graph offers extra context, showing whether observed data points are within the expected range and if they are higher or lower than expected. Manual thresholds are also displayed more clearly.Streamlined Configuration Options
Users can now switch between automatic, ML model-based monitoring and manual, threshold-based monitoring easily. There is also an option to select a specific date to begin incorporating historical data into the model, which is useful if the data has changed significantly over time.Real-time Monitoring and Data Lineage
Metaplane provides real-time monitoring capabilities, enabling immediate alerts and notifications when anomalies are detected. It also offers comprehensive data lineage tracking, helping users understand the origin, transformations, and flow of the data across the pipeline.Snowflake Integration
For Snowflake users, Metaplane captures snapshots of table freshness and row count, providing historical metadata without additional cost. This allows for quick monitoring setup if new tables need to be monitored in the future.Disadvantages of Metaplane’s Data Observability v2
While Metaplane’s Data Observability v2 offers many benefits, there are some potential drawbacks to consider:Cost
Metaplane is a commercial tool that requires a subscription, which may not be suitable for organizations with budget constraints.Feature Limitations
Although Metaplane offers a solid set of features, it might not be as feature-rich or customizable as some open-source alternatives like Great Expectations.Community Support
Compared to open-source tools, Metaplane’s community support is relatively smaller, which could be a disadvantage for users seeking extensive community resources.Removal of Certain Features
The new system has removed the “Alert level” option, and while a new method for fine-tuning the expected range is planned, this change might initially inconvenience some users. By considering these points, users can make an informed decision about whether Metaplane’s Data Observability v2 meets their specific needs and requirements. Data Observability v2 by Metaplane - Comparison with Competitors
Unique Features of Metaplane
- Comprehensive Data Quality Assessment: Metaplane stands out for its robust data quality assessment and alerting mechanisms. It monitors critical data attributes to ensure data accuracy throughout the entire lifecycle, and its intelligent alerting system promptly notifies data teams of any anomalies.
- User-Friendly Interface: Metaplane offers a user-friendly interface that simplifies the process of using the tool, minimizing the learning curve and maximizing productivity for data teams with diverse skill sets and expertise levels.
Alternatives and Comparisons
Validio
- Real-Time Data Monitoring and Anomaly Detection: Validio is a strong alternative that excels in real-time data monitoring and advanced anomaly detection. It also provides deep data lineage tracking, which might be a necessity for organizations with complex data ecosystems. However, Validio may lack the ease of use and comprehensive data quality assessment that Metaplane offers.
- Advanced Features: Validio’s features are more geared towards organizations requiring advanced anomaly detection and detailed data lineage, which could make it a better fit for those with more complex requirements.
Observability 2.0 Tools (General)
- Unified Telemetry Streams: Observability 2.0 tools, such as those described in the Observability 2.0 framework, unify telemetry data (metrics, logs, traces, and events) into a single platform. This provides a comprehensive view of system health and simplifies troubleshooting by correlating data across different types of telemetry. While Metaplane does not explicitly mention unified telemetry streams, Observability 2.0 tools like these offer a more integrated approach to data observability.
- AI-Powered Anomaly Detection: Observability 2.0 tools often employ AI and machine learning to identify anomalies in real-time, enabling proactive issue resolution. This is similar to Metaplane’s intelligent alerting system but may offer more advanced AI-driven insights and dynamic baselines.
Other Data Observability Tools
- CastorDoc: CastorDoc is another tool that integrates advanced governance, cataloging, and lineage features with a user-friendly AI assistant. It enables self-service analytics and simplifies data interaction through natural language, which could be an attractive option for organizations looking for a more integrated data management solution.
Potential Limitations and Considerations
- Customizations and Integrations: Metaplane might require additional customizations or integrations for organizations with complex data ecosystems or specific requirements. This could add to the overall cost and complexity of implementing the tool.
- Advanced Anomaly Detection: While Metaplane has strong data quality assessment capabilities, it may lack the advanced anomaly detection features that some other tools, like Validio, offer. This could be a consideration for organizations that need more sophisticated anomaly detection.
In summary, Metaplane’s Data Observability v2 is strong in data quality assessment and user-friendly interfaces, but it may not offer the same level of advanced anomaly detection or unified telemetry streams as some other tools in the category. The choice between Metaplane and its alternatives depends on the specific needs and priorities of the organization.
Data Observability v2 by Metaplane - Frequently Asked Questions
Frequently Asked Questions about Data Observability v2 by Metaplane
What is Data Observability v2 by Metaplane?
Data Observability v2 by Metaplane is an updated version of their data observability platform. It is designed to provide greater visibility into your data, more predictable alerting behavior, and streamlined data quality tools. This version includes a redesigned monitor page, improved alerting systems, and enhanced visibility into underlying data, particularly for Snowflake customers.What are the key features of the new monitor page in Data Observability v2?
The new monitor page features several enhancements, including a redesigned graph with contextual axes that make it easier to compare historical data and recent data points. The graph now shows the exact values for Metaplane’s predicted range and where the observed value falls. Additionally, the table below the graph provides more context on whether data points are within the expected range and how they have historically behaved. There is also a new “Overview” section and streamlined configuration options.How has alerting behavior changed in Data Observability v2?
In the new system, the expected range on the graph and the range that triggers an alert are the same, resulting in slightly larger expected ranges on the graph. This simplifies the alerting behavior, eliminating the need for an “Alert level” option. If a value falls outside the expected range (the light green area), Metaplane sends an alert.What additional visibility does Data Observability v2 provide for Snowflake users?
For Snowflake users, Metaplane now captures snapshots of the freshness and row count of every table or view in the database. While this does not trigger alerts, it provides historical metadata that can be useful for investigating issues or adding new monitors without the standard 3-5 day training period. This extra context is obtained through Snowflake’s information schema and does not incur additional costs.How does Data Observability v2 help in managing data quality?
Data Observability v2 helps in managing data quality by providing real-time alerts and detailed diagnostics. It ensures that data pipelines run smoothly, minimizing downtime and enhancing data reliability. The platform collects metadata about the properties and relationships of your data, monitors for changes, and presents actionable insights to help resolve data quality issues quickly.What are the four pillars of Data Observability that Metaplane supports?
The four pillars of Data Observability are Metrics, Metadata, Lineage, and Logs. Metrics and Metadata describe the internal and external characteristics of the data itself. Lineage and Logs describe the internal dependencies within the data and its interactions with the external world. These pillars provide a comprehensive view of your data at any point in time.How can I justify the investment in Data Observability v2?
Justifying the investment in Data Observability v2 can be done by calculating the cost savings from reduced time spent on addressing data quality issues. For example, if a team spends five hours a week on data quality issues at $50 per hour, this amounts to over $10,000 annually. A data observability tool like Metaplane can significantly reduce this cost, providing a clear ROI. Additionally, the tool can help in root cause analysis, impact analysis, and other tasks, further justifying the investment.What is the cost of using Metaplane’s Data Observability v2?
The cost of using Metaplane’s Data Observability v2 can vary widely, ranging from approximately $3,000 to $55,000 annually, with an average cost of around $20,000 per year. Prices can be negotiated, and using services like Vendr can help achieve lower prices than those listed on Metaplane’s official website.How does Data Observability v2 compare to traditional data monitoring and testing?
Data Observability v2 differs from traditional data monitoring and testing in several ways. Unlike data monitoring, which requires specifying metrics upfront, data observability provides a historical record of metadata and layers monitoring on top of it. Unlike data testing, which is designed for testing known issues, data observability is designed for identifying and resolving unknown issues across the entire data stack.Can I set up and configure Data Observability v2 quickly?
Yes, Metaplane’s Data Observability v2 is designed to be set up and configured quickly. The platform can be used out-of-the-box within 30 minutes, and it includes streamlined configuration options that make it easier to manage your monitors. For example, you can switch between automatic, ML model-based monitoring and manual, threshold-based monitoring easily.What kind of support and resources are available for Data Observability v2 users?
Metaplane provides various resources and support for its users. This includes detailed documentation, a redesigned UI with clear instructions, and the ability to capture historical metadata for quick setup of new monitors. Additionally, Metaplane’s blog and support pages offer insights and guides on how to use the platform effectively. Data Observability v2 by Metaplane - Conclusion and Recommendation
Final Assessment of Data Observability v2 by Metaplane
Data Observability v2 by Metaplane is a significant advancement in the field of data observability, particularly for organizations relying heavily on data warehouses like Snowflake. Here’s a comprehensive look at its benefits and who would gain the most from using this platform.Key Features and Improvements
Redesigned Monitoring Interface
The new platform features an entirely redesigned monitor page with a more intuitive UI, contextual axes on graphs, and clearer visualizations of historical and recent data points. This makes it easier to identify whether data points are within the expected range without additional mental calculations.
Predictable Alerting Behavior
The system now ensures that the expected range on the graph and the range that triggers alerts are the same, simplifying alert management. This change has also led to slightly larger expected ranges on graphs, providing more clarity on when alerts are triggered.
Enhanced Data Visibility
For Snowflake users, Metaplane captures snapshots of table freshness and row count, providing valuable metadata without additional costs. This allows for quick monitoring of previously unmonitored tables without the usual 3-5 day training period.
Streamlined Configuration
Users can now switch between automatic, ML model-based monitoring and manual, threshold-based monitoring. There is also an option to select a specific date to begin incorporating historical data into the model, which is useful if data has materially changed over time.
Who Would Benefit Most
Data Engineers and Analysts
These professionals will appreciate the intelligent auto-monitoring capabilities, automatic suggestions for deeper monitoring, and quick insights into warehouse spend. These features help in maintaining high data quality and performance, which is crucial for their daily tasks.
Enterprise Leaders
Leaders in businesses that rely on data warehouses for decision-making will benefit from the end-to-end visibility and actionable alerts provided by Metaplane. This ensures that critical data applications, especially those involving AI and ML, operate with high reliability and data trust.
Teams in Regulated Industries
Organizations in highly regulated industries such as finance, healthcare, and technology will find Metaplane’s integration with Snowflake’s secure environment beneficial. It helps in maintaining compliance standards like SOC 2 and HIPAA by ensuring critical data processing occurs within a secure environment.
Overall Recommendation
Data Observability v2 by Metaplane is a strong choice for any organization seeking to improve data quality, reliability, and performance. Its enhanced features, such as more predictable alerting behavior, greater visibility into underlying data, and streamlined configuration options, make it an invaluable tool for data teams.
Given its seamless integration with Snowflake and the ability to capture valuable metadata without additional costs, Metaplane stands out as a comprehensive solution for data observability. It is particularly recommended for businesses that are heavily invested in AI and ML initiatives, as it ensures that the data powering these initiatives is trustworthy and of high quality.
In summary, if you are looking to enhance your data observability, improve data trust, and ensure the reliability of your data applications, Data Observability v2 by Metaplane is an excellent choice.