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Integration & Connectivity
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ConnectivityIntegrates with SaaS, databases, cloud platforms, and on-premises systems as required by the customer.
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BI Tool ConnectivityIntegrates with BI tools for insights and reporting
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Cross-Platform IntegrationSupports diverse platforms and environments including cloud, on-premise and hybrid deployments
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Comprehensive API AccessProvides API access for integration with other tools and automation scripts.
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Data Quality & Monitoring
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Incremental ProfilingSupports continuous profiling for real-time monitoring.
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Data Corruption DetectionIdentifies corrupted data and prevents its propagation through automation flow conroles
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Data Quality Rules Definition Allows defining data quality rules through an intutive interface
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Data Quality Rules PredictionProvides and out of the box facility for predicting the data quality problems, creating out of the box data quality rules
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Schema Drift DetectionAutomatically detects changes in the data schema, ensuring consistency with the expected schema structure.
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Anomaly DetectionIdentifies unusual patterns in the data that could indicate data quality issues or system anomalies.
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Data Quality MonitoringMonitors the quality of the data, ensuring it adheres to predefined rules and expectations.
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Freshness CheckChecks the freshness of the data to ensure it is up-to-date and ready for consumption.
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Support for Custom Data Quality MetricsSupports defining and monitoring custom data quality metrics.
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Support for Cyclic Barriers in Quality Failures
Prevents cascading failures in data quality issues.
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Cycle Breaker CapabilityPrevents infinite loops in data pipelines.
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Ability to Set Priority in Quality RulesAllows users to prioritize critical data quality checks and the order of priority
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Real-Time MonitoringProvides an integrated Monitoring capability to monitor for compliance to the various parameters
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Integration with Pipeline SchedulersDoes the tool provide any integration with pipeline schedulers to stop/pause pipelines based on observed values
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Observability & Pipeline Health
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Rescue Data Within PipelinesMechanisms for recovering data within pipelines.
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Root Cause Analysis (RCA) MetricsOffers metrics for diagnosing data issues. Does the tool offer an intutive user experience for the same?
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Insights and Alerts for Root Cause AnalysisProvides actionable alerts for resolving issues.
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Pattern MiningDetects recurring data issues or trends.
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Pushdown CustomizationsOffers flexibility to push computations to underlying data systems.
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Data Volume ScalabilityScales efficiently with increased data volume.
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End-to-End Data Pipeline ObservabilityTracks the entire data pipeline lifecycle.
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Alerts customizationCustomizable alerts via various channels (email, SMS, Slack, etc.), with configurable thresholds.
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Visualization of Data PipelinesProvides visual representations of data flows and dependencies.
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Governance, Compliance & Security
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Data SovereigntyEnsures compliance with data regulations (GDPR, HIPAA, etc.). Also is any data moved to the Observability vendors cloud?
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Data MovementDoes the tool move/process data in their cloud data centers? if Yes, how is the data being secured/
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Data ProcessingDoes the tool allow processing of data in organizations internal data engines as required?
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Governance and Compliance SupportEnsures compliance with industry standards and regulatory requirements.
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Role-Based Access Control (RBAC)Provides role-based access to ensure security.
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Audit Logs and VersioningTracks historical changes and maintains audit logs.
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Data Retention and Archival PoliciesSupports long-term storage and access to observability data.
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Performance & Scalability
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Choice of Compute Systems for Observability
Flexibility in selecting compute platforms. Example Snowflake,Databricks , Spark or standard compute to perform the observability task
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Dependency on Compute PlatformDoes the tool offer a vendor agnostic compute platform. Minimal reliance on specific compute platforms.
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Operational Infrastructure CostsBalances cost with infrastructure needs.
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Speed of Policy Execution (Correctness vs Speed)
Offers flexibility in prioritizing speed or accuracy.
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Performance vs AccuracyBalances speed and accuracy for policy execution.
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Scalability Across PlatformsScales across cloud or on-premises systems.
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Handling large volume of dataPerformance in environments with large datasets and high-throughput data pipelines.
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Streaming Data SupportSupports real-time observability of streaming data.
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Automation & Intelligence
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Anomaly Prediction with Machine LearningUses ML to predict potential anomalies.
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Automated Issue ResolutionAutomatically resolves common data issues.
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Automated DocumentationGenerates automated reports and documentation.
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Asynchronous Policy ExecutionAllows asynchronous execution of policies for non-blocking operations.
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Data Lineage & Dependency Tracking
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Trusted LineageTracks data lineage across systems and pipelines and able to display it back in the UI while performing analysis on data issues
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Integration with Metadata/CatalogsIf the tool automatically doesnt capture lineage, does it have OOTB integration with industry standard catalog/metadata players
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Cross-System Data Dependency TrackingMonitors dependencies between different systems.
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Code Change Tracking for AnomaliesDetects anomalies introduced by code changes in data pipelines.?
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User Experience & Customization
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Customizable Dashboards and ReportingProvides customizable reporting and dashboards for monitoring.
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Self-Serve CapabilitiesOffers self-service functionality for non-technical users.
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Collaboration FeaturesSupports collaboration between teams with shared dashboards, annotations, etc.
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Custom Alerting MechanismsAllows configuring custom alerts based on thresholds or rules.
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Integration with Incident Management Systems
Integrates with systems like PagerDuty, Jira, or Opsgenie for issue tracking.
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Vendor Relationship & Exit Strategy
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Exit Criteria from the Observability Vendor
Identify and flag native and properietary flows. This will be critical in case the observability tools need to be migrated how can the logic and the code be mgirated. Clearly defined exit strategy for switching vendors.
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Price to Value (ROI) VisibilityOffers a balance between cost and the value delivered.
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Deployment FlexibilitySupport for on-premises, cloud, and hybrid environments, as well as containerized deployments.
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Cost StructureTransparency and flexibility in pricing models, including the total cost of ownership (TCO)
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Licensing OptionsLicensing terms that fit the organization’s needs, including per-user, per-node, or usage-based pricing.
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FinOpsDoes the tool have built in Fin-Ops construct helping users undertand where the observabilty task should be run and/or intelligent distribution of workloads optimizing cost
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