Product blogs archive
Thoughts on the future
of data infrastructure.
EngineeringBest practices for agentic data product offices: a field guide for CDOs and data product ownersEngineeringBest practices for agentic data platforms: a field guide for platform and fleet data teamsEngineeringBest practices for agentic GenAI training data: a field guide for data curation and eval teamsEngineeringBest practices for agentic location and marketplace data: a field guide for marketplace and geospatial data teamsEngineeringBest practices for agentic risk and regulatory reporting data: a field guide for risk and regulatory reporting data teamsEngineeringBest practices for agentic supply planning and inventory data: a field guide for supply planning data teamsEngineeringBest practices for agentic telematics data: a field guide for connected-vehicle and UBI teamsEngineeringBest practices for agentic viewership data: a field guide for streaming and audience data teamsEngineeringBest practices for agentic ads data marts: a field guide for measurement data teamsEngineeringBest practices for agentic card and payment transaction data: a field guide for payments data teamsEngineeringBest practices for agentic clinical data: a field guide for EHR and research data teamsEngineeringBest practices for agentic market and reference data: a field guide for market and reference data teamsEngineeringBest practices for agentic physical AI data: a field guide for robotics and perception data teamsIndustryThe agentic data platform for financial services: regulatory reporting, lineage and change evidence on autopilotIndustryThe agentic data platform for retail and e-commerce data teamsEngineeringBest practices for agentic fund accounting and investment data: a field guide for investment data teamsEngineeringBest practices for agentic product usage and billing data: a field guide for usage and billing data teamsIndustryData Agent Evals Report 2026EngineeringHow Large Companies Evaluate Data Agents in ProductionEngineeringBest practices for agentic claims data: a field guide for payer and clearinghouse data teamsEngineeringBest practices for agentic clinical trial and R&D data: a field guide for clinical and R&D data teamsEngineeringBest practices for agentic retail data products: a field guide for retail media and insights teamsEngineeringBest practices for agentic agricultural and machine data: a field guide for machine data teamsEngineeringBest practices for agentic pharma commercial data: a field guide for launch and RWD teamsEngineeringBest practices for agentic public program and government data: a field guide for government data teamsComparisonUpriver vs Data Workers: Your Data Never Leaves the United StatesEngineeringBest practices for agentic clickstream data: a field guide for event platform and product analytics teamsEngineeringBest practices for agentic data acquisition: a field guide for foundation model data teamsEngineeringBest practices for agentic underwriting and claims data: a field guide for underwriting and claims data teamsEngineeringBest practices for agentic sales data: a field guide for RevOps and revenue data teamsIndustryThe agentic data platform for healthcare and life sciencesEngineeringBest practices for agentic Customer 360 and CDP data: a field guide for Customer 360 and CDP teamsEngineeringBest practices for agentic people and labor-market data: a field guide for people and workforce data teamsEngineeringBest practices for agentic shipment and logistics network data: a field guide for logistics data teamsEngineeringBest practices for agentic sales data marts: a field guide for sales data product teamsEngineeringBest practices for agentic security and observability telemetry: a field guide for security and observability data teamsEngineeringBest practices for agentic smart meter and grid data: a field guide for utility data teamsIndustryYou just became Head of Data Products. Here is a 90-day plan that runs on agents.IndustryWhy Data Workers changes how revenue teams build sales data productsProductEstimating the Productivity of an Autonomous Agentic Data PlatformComparisonDatabricks Genie Ontology vs Data Workers: Context for Genie, or One Governed Context for the Whole EstateComparisonMonte Carlo vs Data Workers: detection vs resolutionComparisonData Workers on Microsoft Fabric: what it adds to data agents, Copilot and Fabric IQComparisonSnowflake Horizon Catalog vs Spellbook Data Catalog: Horizon Enforces the Grants, Data Workers Governs the WorkComparisonData Workers on AWS: The Agentic Data Platform on Top of Redshift, Glue, S3 Tables and SageMakerComparisonImmuta vs Cyera, and where the Data Security agent fitsComparisonAI data engineering agents compared: nao, Datus, definity and Mica AI vs Data WorkersIndustryYour Pipelines Run on Airflow. Now Let Data Workers Own What They Produce: A Guide for Data LeadersIndustryYour Company Runs on Alation. Now Let Data Workers Keep What It Shows True: A Guide for Data LeadersIndustryYour Company Runs on Atlan. Now Let Data Workers Keep What It Shows True: A Guide for Data LeadersTutorialFrom AWS to an Autonomous Data Platform: A Stage-by-Stage PlaybookTutorialFrom Microsoft Fabric to an Autonomous Data Platform: A Stage-by-Stage PlaybookIndustryYou Built on AWS. Now Make Your Whole Estate Agentic & Autonomous with Data WorkersIndustryYour Governance Office Runs on Collibra. Now Let Data Workers Keep the Estate True to It: A Guide for Data LeadersIndustryYour Company Runs on Datadog. Now Let Data Workers Fix the Data Behind Every Alert: A Guide for Data LeadersIndustryYour Team Standardized on dbt. Now Let Data Workers Run the Work Around the Project: A Guide for Data LeadersIndustryYour Company Standardized on Fivetran and dbt. Now Let Data Workers Own Whether the Data Is Right: A Guide for Data LeadersIndustryYou Built on Microsoft Fabric. Now Make Your Whole Estate Agentic & Autonomous with Data WorkersComparisonAtlan vs Spellbook: The Agentic Data Catalog, Inventory vs Control PlaneIndustryHow to Automate Your Entire Data Operations as a Large EnterpriseTutorialThe Autonomous Data Platform Playbook: How Data Workers Turns Data Engineering Copilots Into an Agentic Data PlatformTutorialHow to Automate Monte Carlo Alerts: A Stage-by-Stage Playbook with Data WorkersIndustryData Engineering Agents in 2026: What Data Leaders Need on Top of the CopilotProductAgent Bricks Supervisor Agent MCP: Add Data Workers Agents as Supervisor ToolsProductAirflow Integration for AI Agents: How Data Workers Works Through Airflow's REST APIProductData Workers + Claude Code, Cursor and Codex: The MCP Server for Data Engineering in Your Coding AgentProductCortex Agents MCP: Connect Data Workers to Snowflake CoWork as an MCP ConnectorProductData Workers + Cube, AtScale, MetricFlow and Apache Ossie (OSI): One Governed View Across Every Semantic LayerProductDagster and Prefect Integration for AI Agents: How Data Workers Works Through Your Runs and FlowsProductData Workers + dbt: A dbt Integration Where AI Agents Work Through Your ProjectProductData Workers + Fivetran: A Fivetran Integration That Catches Schema Changes Before They Break Your ModelsProductData Workers + Hex and ThoughtSpot: Making Sure the AI Analyst's Answer Is RightProductGemini Enterprise Custom MCP Server: Bring Data Workers into Gemini Enterprise and ADKProductData Workers + Monte Carlo: A Monte Carlo Integration That Turns Alerts Into Verified FixesProductData Workers + OpenLineage: An OpenLineage Integration That Closes the Loop on Failed RunsProductData Workers + Tableau, Power BI and Looker: A BI Integration That Checks the NumberProductGenie MCP Server: Connect Genie One and Genie Agents to Data Workers in Both DirectionsProductHive and Glue to Unity Catalog Migration With Parity Checks: A How-To Over MCPProductKnowledge Catalog Business Glossary and Aspects in Data Context Wizard: A How-ToProductLookML to Data Context Wizard: Give Every Agent Your Looker Definitions, Checked Against dbtIndustryYou're on Monte Carlo. Now Let Data Workers Fix What It Finds: A Guide for Data LeadersProductSnowflake and Databricks Lineage, Traced as One Path: A Cross-Cloud How-To Over MCPProductSnowflake Data Quality Alerts to the Autonomous Data-Conductor: Route Failed DMF Expectations to a Verified FixProductSnowflake Semantic Views over MCP: Connect Them to Data Context Wizard and Settle Metric ConflictsProductUnity Catalog Metric Views and Lineage in Data Context Wizard: A How-To Over MCPIndustryThe agentic data platform for energy and utilities data teamsIndustryThe agentic data platform for insurance: bordereaux, claims, reserving and pricing data on autopilotIndustryThe agentic data platform for manufacturing data teamsIndustryThe agentic data platform for media and advertising data teamsIndustryThe agentic data platform for the public sector: benefits, health, transportation and open data on autopilotIndustryThe agentic data platform for SaaS and tech companiesIndustryThe agentic data platform for telecommunications data teamsProductYour company just rolled out AI assistants. Now what?ProductWhat do the autonomy levels mean, from L0 to L4?ProductBring your own context: plug your ontologies, semantic layers and knowledge graphs into Data WorkersProductCan't we just build this ourselves with Claude Code and a few MCP servers?IndustryYour Company Rolled Out ChatGPT Enterprise. Now Make Your Data Estate Agentic & Autonomous with Data WorkersIndustryYour Company Rolled Out Claude. Now Make Your Data Estate Agentic & Autonomous with Data WorkersIndustryData Workers for analytics engineersIndustryData Workers for chief data officersIndustryData Workers for CIOs and CTOsIndustryData Workers for CISOsIndustryData Workers for data analystsIndustryData Workers for data engineersIndustryData Workers for data governance leadsIndustryData Workers for data platform engineersIndustryData Workers for FinOps leadsIndustryData Workers for ML engineersIndustryData Workers for VPs and heads of dataProductCan Data Workers run in our VPC or air-gapped?ProductWhat integrations does Data Workers support? Every category, what it reads and what it can changeProductHow does Data Workers help with SOX, HIPAA, GDPR and the EU AI Act?ProductHow is Data Workers different from a data catalog?ProductHow is Data Workers different from data observability?ProductHow does Data Workers work with the coding agents we already use?ProductWhat happens in the first 90 days?ProductHow do approvals work in practice?ProductAI agents hallucinate. How does Data Workers get it right on our data?ProductHow does Data Workers handle PII?ProductHow do we get our team to trust agents?ProductHow do you measure whether the agents are doing a good job?ProductHow do we roll back an agent's change?ProductIs it safe to let AI agents change production data?ProductWhat's the ROI of agentic data operations?ProductWhat does a pilot look like?ProductWhat if Data Workers goes away? What you own, what you subscribe to, and how to leaveProductWhat is an agentic data platform?ProductWhere does our data go? Security, privacy and deployment with Data WorkersProductWhich model does Data Workers use, and what does it cost to run?ProductWho owns the agents?ProductWhy a swarm of specialist agents instead of one big agent?ProductWhy is there no usage meter on Data Workers?ProductWhy now? Three changes that make agentic data operations practical in 2026ProductWill Data Workers replace my data team?ProductYou're on Acceldata: Its Agents Watch Pipelines, Quality and Spend. Data Workers Fixes the Cause Across Your EstateProductYou're on Actian Data Intelligence: Keep Your Data Products True, With Data Workers Doing the Operations WorkProductYou're on Aider: it writes the change on a branch, Data Workers carries it into productionProductYou're on Airbyte: It Moves the Data In From 700+ Sources. Data Workers Owns Whether What Lands Is RightProductYou're on Airflow: Keep Running the Schedule, and Let Data Workers Run the Operations When a DAG Run Goes WrongProductYou're on Alation: Keep the Reading Room, Add the Crew That Keeps It TrueProductYou're on Alteryx: Your Analysts Build the Workflows. Data Workers Owns Whether the Data They Read and Write Is RightProductYou're on ALTR: ALTR Masks and Tokenizes Sensitive Data Where It Sits. Data Workers Keeps the Data Around Those Policies RightProductYou're on Amazon Kinesis and MSK: They Carry Your Events on AWS. Data Workers Owns Whether What Lands Is RightProductYou're on Amazon Neptune: Keep Your AWS Knowledge Graph True, From the Redshift Feed to the GraphRAG AnswerProductYou're on Amazon Q Developer: give it governed data context and approved data changesProductYou're on Amplitude: It Shows How People Use Your Product. Data Workers Owns Whether the Data Behind Those Charts Is RightProductYou're on Amundsen: The Project Is Archived. Keep the Search, Add the Control Plane Behind ItProductYou're on Anomalo: It Finds What No Rule Caught. Data Workers Fixes It and Proves ItProductYou're on Apache Flink: It Computes on Every Event as It Arrives. Data Workers Owns Whether What Your Jobs Write Is RightProductYou're on Apache Kafka: It Is the Event Backbone Your Platform Team Runs. Data Workers Owns Whether What Consumers Land Is RightProductYou're on Argo Workflows: Your Platform Team Runs Data and ML Workflows on Kubernetes. Data Workers Does the Operations Work on What They ProduceProductYou're on Astronomer: Keep Astro and Otto on the DAG, and Let Data Workers Follow the Incident Out of ItProductYou're on Ataccama: ONE Governs Quality, Master Data and the Catalog. Data Workers Repairs the Cause Upstream and Proves ItProductYou're on Atlan: Keep What Your Catalog Shows True, With Data Workers Doing the Operations WorkProductYou're on AtScale: Keep One Semantic Model True for Excel, Power BI, Tableau and Every AgentProductYou're on Augment Code. Here's how Data Workers builds on itProductYou're on AWS DMS: It Moves Your Databases Into AWS. Data Workers Owns Whether What Lands Is Right and Holds the CutoverProductYou're on AWS Glue Data Catalog and SageMaker Catalog: AWS Registers and Shares Your Data. Data Workers Keeps It TrueProductYou're on Azure Data Factory: Keep Moving the Data, and Let Data Workers Run the Operations When a Pipeline Run Delivers It WrongProductYou're on Bigeye: It Drafts the Remediation SQL. Data Workers Fixes the Data and Proves ItProductYou're on BigID: BigID Finds and Classifies Sensitive Data Everywhere. Data Workers Keeps the Pipelines Carrying It RightProductYou're on Boomi: It Connects Your Applications and Processes. Data Workers Owns Whether the Data They Deliver Is RightProductYou're on Census: Census Sends Your Models to the Tools Your Teams Act On. Data Workers Makes Sure Each One Is Right FirstProductYou're on ChatGPT Enterprise: Connect Data Workers Over MCP So Every Answer Comes From Governed DataProductYou're on Chroma: Know What Went Into Every Collection, and Keep It True as the Sources ChangeProductYou're on Claude: Claude for data teams, with Data Workers as the connector that does the workProductYou're on ClickHouse: It Answers Real-Time Analytics Questions in Milliseconds. Data Workers Owns Whether the Data Behind Those Answers Is RightProductYou're on Cline. Here's how Data Workers builds on itProductYou're on Cloudera: It Runs Your Enterprise's Hybrid Data Estate. Data Workers Owns Whether the Data in It Is Right, Behind ApprovalsProductYou're on Coalesce: Your Team Designs the Pipeline There, Column by Column. Data Workers Runs Operations on It in ProductionProductYou're on Coalesce Catalog (formerly CastorDoc): Business Users Trust What It Shows. Data Workers Keeps It TrueProductYou're on Coalesce Quality (formerly SYNQ): It Watches Your Data Products. Data Workers Fixes What Breaks ThemProductYou're on Codex: give it governed data context and approved data changesProductYou're on Cognee: Keep What Your Agents Recall About Data True Against the WarehouseProductYou're on Collibra: Your Governance Office Sets the Policy. Data Workers Keeps the Estate True to ItProductYou're on Collibra Data Quality: It Scores Quality Inside Your Governance Platform. Data Workers Fixes the Cause and Proves ItProductYou're on Confluent: It Moves Your Events in Real Time. Data Workers Owns Whether What Lands Downstream Is RightProductYou're on Contextual AI: Ground the Documents There, Govern the Numbers With Data WorkersProductYou're on Control-M: Your Enterprise Schedules and Governs Batch Across Mainframe, ERP and Cloud. Data Workers Does the Operations Work on the Data Those Jobs ProduceProductYou're on Cube: Let Agents Edit the Semantic Model, With Every Change Checked Against the Data Under ItProductYou're on Cursor. Here's how Data Workers builds on itProductYou're on Cyera: Cyera Finds the Exposure. Data Workers Closes It Where the Data Is MadeProductYou're on Dagster: Keep Every Asset Right, With Data Workers Doing the Repair Work Behind ApprovalsProductYou're on data.world: The Knowledge Graph Gives Everyone the Context. Data Workers Keeps It TrueProductYou're on Databricks Genie Ontology: Keep Curating It, and Let Data Workers Keep It True Across Every EngineProductYou're on Datadog: It Sees the Data Incident. Data Workers Fixes It and Proves the FixProductYou're on Datafold: Prove Every Change Before Merge, and Let Data Workers Run Production After ItProductYou're on DataGalaxy: Keep Every Data and AI Product True, With Data Workers Doing the Operations WorkProductYou're on DataHub: Keep the Open Map, Add the Control Plane That Keeps It TrueProductYou're on dbt: dbt Defines and Tests Your Models. Data Workers Runs the Operations Around ThemProductYou're on the dbt Semantic Layer: Keep Every Copy of Every Metric True, for People and AI AgentsProductYou're on Debezium: It Streams Every Committed Change Out of Your Databases. Data Workers Owns Whether What Those Changes Become Downstream Is RightProductYou're on Devin: keep it shipping code tickets, and give it governed data context and approved data changesProductYou're on dlt: Your Engineers Load Anything With It. Data Workers Owns Whether What It Loaded Is RightProductYou're on Domo: Your Business Teams Run on Cards, Dataflows and Agents. Data Workers Owns Whether the Data Feeding Them Is RightProductYou're on DQLabs (PRIZM): It Ranks Every Issue by Business Impact. Data Workers Ships the Verified FixProductYou're on Dremio: It Accelerates Your Iceberg Lakehouse. Data Workers Keeps What It Accelerates TrueProductYou're on Dynatrace: It Root-Causes the Problem. Data Workers Fixes the Data the Problem Left BehindProductYou're on Elastic: Kibana Fires the Alert. Data Workers Fixes the Data Behind ItProductYou're on Elementary: It Opens the dbt Fix PR. Data Workers Carries the Fix Through the Stack and Proves ItProductYou're on Estuary: It Moves Data in Real Time From Databases and SaaS. Data Workers Owns Whether What Lands Is RightProductYou're on Fabric IQ: Bring Your Ontology Into Data Workers So Every Agent Reads One Owned MeaningProductYou're on Factory: give Droids governed data context and approved data changesProductYou're on Firebolt: It Serves Your Customers' Analytics in Milliseconds. Data Workers Owns Whether Those Answers Are RightProductYou're on Fivetran: Fivetran Moves the Data In. Data Workers Owns Whether What Landed Is RightProductYou're on Gable: Gable Guards the Producer's Pull Request. Data Workers Owns What Gets ThroughProductYou're on Gemini CLI: give it governed data context and approved data changesProductYou're on Gemini Enterprise: what changes when your people can ask Data WorkersProductYou're on GitHub Copilot: Copilot for data pipelines, with Data Workers carrying every data change into productionProductYou're on Glean: Add the Data Estate's Context So Every Agent Answers With the Thread and the PipelineProductYou're on GoodData: It Serves Every Tenant Governed Analytics From Code. Data Workers Owns Whether the Data Under Each Tenant's Numbers Is RightProductYou're on Google Antigravity. Here's how Data Workers builds on itProductYou're on Managed Service for Apache Airflow (Formerly Cloud Composer): Let Google Run Airflow, and Let Data Workers Run the Operations When a DAG Run's Output Goes WrongProductYou're on Google Knowledge Catalog: Turn the Context You Curate Into Fixes Your Stewards ApproveProductYou're on goose. Here's how Data Workers builds on itProductYou're on Grafana: It Shows the Alert. Data Workers Fixes the Data Behind ItProductYou're on Great Expectations: GX Core Is the Test. Data Workers Fixes What Fails ItProductYou're on Greenplum: It Runs Your MPP Analytics. Data Workers Owns Whether the Data Behind It Is Right, in Place or Through a MoveProductYou're on Hex: Your Analysts and Data Scientists Answer There. Data Workers Owns Whether the Data Behind Every Answer Is RightProductYou're on Hightouch: Hightouch Activates Your Warehouse Data. Data Workers Owns Whether What It Sends Is RightProductYou're on IBM Netezza: It Runs the Warehouse Workloads You've Trusted for Years. Data Workers Owns Whether What It Serves, and What Leaves It, Is RightProductYou're on Immuta: Immuta Decides Who Sees the Data. Data Workers Makes Sure the Data It Protects Is RightProductYou're on incident.io: Run the Response There, Fix the Data With Data WorkersProductYou're on Informatica: IDMC Governs and Moves Your Data. Data Workers Keeps It True Everywhere It LandsProductYou're on Informatica Data Quality: It Runs the Rules Inside IDMC. Data Workers Fixes What Fails Them Across the EstateProductYou're on Informatica PowerCenter: It Runs Your Long-Lived ETL. Data Workers Keeps What It Loads Right Through the Move to IDMCProductYou're on Jedify: Keep the Context Graph, and Keep the Data Under Every Answer RightProductYou're on JetBrains AI and Junie. Here's how Data Workers builds on itProductYou're on Jira: Keep Planning the Data Team's Work There, Let Data Workers Do the Data Work and Close It With ProofProductYou're on Jira Service Management: Keep the Queue, Let Data Workers Resolve the Data Incident Behind the TicketProductYou're on Kaelio's ktx: Keep the Data Under Every Approved Measure Right, Across the Whole LifecycleProductYou're on Keebo: It Tunes the Warehouse. Data Workers Keeps What the Warehouse Produces RightProductYou're on Kestra: Your Team Declares and Runs Event-Driven Flows. Data Workers Does the Operations Work When a Flow's Output Goes WrongProductYou're on Kiro. Here's how Data Workers builds on your specsProductYou're on Letta: Give Long-Running Data Agents Governed Context and a Safe Way to Change DataProductYou're on Lightdash: Your dbt Project Is Your BI. Data Workers Owns Whether the Data in Those Models Is RightProductYou're on Lightup: It Proves the Two Tables Disagree. Data Workers Makes Them Agree AgainProductYou're on Linear: Keep Planning and Triage There, Let Data Workers Do the Data Work Behind Each IssueProductYou're on Looker: LookML Defines Your Metrics. Data Workers Owns Whether the Data Under Them Is RightProductYou're on Mage: Your Team Builds and Runs Pipelines in Blocks. Data Workers Does the Operations Work When the Output Goes WrongProductYou're on Materialize: It Keeps Your SQL Views Fresh as the Data Changes. Data Workers Owns Whether What Those Views Serve Is RightProductYou're on Matia: One Platform Moves and Watches Your Data. Data Workers Owns the Fix Across Everything Around ItProductYou're on Matillion: Your Team and Maia's Agents Build and Run the Pipelines. Data Workers Owns Whether What They Deliver Is RightProductYou're on Meltano: Your Team Runs Singer Pipelines as Code. Data Workers Owns Whether What They Load Is RightProductYou're on Mem0: Keep What Your Agents Remember About Data True, With Governed Context Next to MemoryProductYou're on Memgraph: Keep the Live Graph True, From the Kafka Event to the GraphRAG AnswerProductYou're on Metabase: Every Team Asks Its Own Questions. Data Workers Owns Whether the Answers Are TrueProductYou're on Metaphor: Your People Find and Discuss Data There. Data Workers Keeps It TrueProductYou're on Microsoft 365 Copilot: Copilot answers your data questions in Teams, and Data Workers does the data work behind itProductYou're on Microsoft Copilot Studio: Add Data Workers as an MCP Tool So Every Agent Answers From Governed DataProductYou're on Microsoft Entra: Entra Decides Who People and Agents Are and What They Can Reach. Data Workers Makes Your Warehouse MatchProductYou're on Microsoft Purview: Purview Classifies and Governs Your Microsoft Estate. Data Workers Fixes What Its Rules FlagProductYou're on Microsoft Teams: Keep the Data Platform Channel, Add the Responder That Fixes the DataProductYou're on Mistral Le Chat Enterprise, now Mistral Vibe: Vibe is where your people ask, and Data Workers makes the answers rightProductYou're on Mixpanel: It Shows What Users Do in Your Product. Data Workers Owns Whether the Warehouse Data Synced Into It Is RightProductYou're on Mode: Your Analysts Write the SQL, Python and Reports. Data Workers Owns Whether the Data Those Reports Query Is RightProductYou're on MongoDB Atlas: It Runs Your Applications' Document Data. Data Workers Owns Whether the Data That Leaves It for Analytics and AI Is RightProductYou're on Monte Carlo: It Finds and Triages the Incident. Data Workers Resolves It, From Day OneProductYou're on MotherDuck and DuckDB: They Make Analytics Fast and Small. Data Workers Owns Whether the Data in Them Is RightProductYou're on MuleSoft: It Connects Your Systems and Governs Your Agents. Data Workers Owns Whether the Data Its Flows Deliver Is RightProductYou're on Neo4j: Keep Your Knowledge Graph True, From the Warehouse Feed to the GraphRAG AnswerProductYou're on New Relic: It Watches the Stream. Data Workers Fixes the Data Behind the AlertProductYou're on Notion AI: Keep Every Metric Definition and Runbook in Notion True to the DataProductYou're on Okta: Okta Decides Who People and Agents Are. Data Workers Checks What Can Still Reach the WarehouseProductYou're on Omni: One Governed Model, Spreadsheet-Speed Analysis. Data Workers Owns Whether the Data Under It Is RightProductYou're on OneTrust: OneTrust Records What You May Do with Personal Data. Data Workers Makes Sure Your Pipelines Honour ItProductYou're on GraphDB (Graphwise, Formerly Ontotext): Keep Your RDF Knowledge Graph TrueProductYou're on Open Semantic Interchange, Now Apache Ossie: What the Standard Settles and What Runs on Top of ItProductYou're on OpenCode: give it governed data context and approved data changesProductYou're on OpenMetadata: Keep the Open Map, Add the Control Plane That Fixes What Its Tests FindProductYou're on Opsgenie: Plan the Move to Jira Service Management Without Breaking Your Data RunbooksProductYou're on Oracle: It Holds Your Systems of Record. Data Workers Keeps Every Copy of Them RightProductYou're on OSI Semantics: Keep Your Ossie YAML True in Every Engine, With an Owner on Every DefinitionProductYou're on OvalEdge: Keep the Governance Suite, Add the Control Plane That Keeps It TrueProductYou're on PagerDuty: Page the Right Person, Then Let the First Responder Fix the DataProductYou're on Palantir Ontology: Bring It to Every Agent, and Keep It True to the Data UnderneathProductYou're on Paradime: Your Team Writes, Ships and Schedules dbt There. Data Workers Runs Operations Across the Estate When Production BreaksProductYou're on Perplexity Enterprise: Connect Data Workers So Internal Numbers Come From Governed DataProductYou're on Pinecone: Keep Every Index True to Its Source, From the Warehouse Table to the RAG AnswerProductYou're on Postgres: It Runs Your Applications and Often Your First Analytics. Data Workers Owns Whether the Data In and Out of It Is RightProductYou're on Power BI: It's How the Business Reads Its Numbers. Data Workers Owns Whether the Data in Its Semantic Models Is RightProductYou're on Prefect: Your Team Writes and Runs the Flows. Data Workers Does the Operations Work When One Goes WrongProductYou're on Privacera, Now Trust3 AI: It Enforces the Policy. Data Workers Keeps the Data Under It RightProductYou're on Promethium: Keep Every Federated Answer Right, From the Source System to the Mantra ReplyProductYou're on PuppyGraph: Keep the Graph Right by Keeping the Tables and the Mapping Under It RightProductYou're on Qdrant: Keep the Payloads Your Filters Trust True, From the Source Table to the Retrieved ChunkProductYou're on Qlik: It Turns Associative Analytics Into Decisions Across the Business. Data Workers Owns Whether the Data Loaded Into Those Apps Is RightProductYou're on Qlik Replicate: It Streams Every Change Out of Your Core Systems. Data Workers Owns Whether What Lands Is RightProductYou're on Qualytics: It Infers and Enforces the Checks. Data Workers Diagnoses, Fixes and Verifies Behind ApprovalsProductYou're on Redpanda: It Streams Your Events With Kafka Compatibility. Data Workers Owns Whether What Lands Downstream Is RightProductYou're on RelationalAI: Keep the Snowflake Data Under Your Semantic Model True, So Every Solve Is RightProductYou're on Replit Agent: Make Every Internal App and Dashboard Your Teams Build Read Governed, Correct DataProductYou're on Rill: Your Metrics Views Answer in Milliseconds. Data Workers Makes Sure the Data Feeding Them Is RightProductYou're on RisingWave: It Keeps Your Streaming Views Fresh. Data Workers Owns Whether What They Serve Is RightProductYou're on Rivery: It Moves and Orchestrates Your SaaS and Database Data. Data Workers Owns Whether What Lands Is RightProductYou're on Roo Code. Here's how Data Workers builds on itProductYou're on RudderStack: It Collects Your Customer Events and Builds Profiles in Your Warehouse. Data Workers Owns Whether What Lands and Flows Out Is RightProductYou're on SailPoint: SailPoint Certifies Who Should Have Access. Data Workers Makes Sure the Warehouse and the Data Still MatchProductYou're on Salesforce Agentforce: Keep the Data Under Every Agent Right, From the Warehouse to Data 360ProductYou're on Salesforce Data 360 (formerly Data Cloud): Keep Every Insight and Segment True to the Warehouse Behind ItProductYou're on SAP Business Data Cloud: Keep Every Model Built on SAP Data Products True to SAP's MeaningProductYou're on SAP BW and Datasphere: Move to Business Data Cloud Before the 2027 Deadline and Keep Every Report RightProductYou're on Satori: Satori Decides What Each Person Sees at Query Time. Data Workers Owns Whether What They See Is RightProductYou're on Secoda: Keep Every Answer True, With Data Workers Doing the Operations WorkProductYou're on Securiti: Securiti Maps the Sensitive Data and Enforces the Controls. Data Workers Owns Whether Your Pipelines Follow ThroughProductYou're on Segment: It Collects and Routes Every Customer Event. Data Workers Owns Whether What They Become Is RightProductYou're on SELECT: SELECT Tells You Which dbt Model Costs What. Data Workers Makes Sure the Cheaper Version Still Returns the Right RowsProductYou're on Select Star: Keep the Map of Your Data True, With Data Workers Doing the Operations WorkProductYou're on ServiceNow: Keep the Incident and the Change Record, Let Data Workers Fix the Data Behind the TicketProductYou're on ServiceNow AI Agents: Route the Data Incident, Then Close It With a ReceiptProductYou're on Sifflet: Sage Finds the Cause and Forge Routes It. Data Workers Fixes It and Proves ItProductYou're on Sigma: Spreadsheet Analysis Runs on Your Warehouse. Data Workers Keeps What's in the Cells Right, Including What People Write BackProductYou're on SingleStore: It Runs Real-Time Transactions and Analytics in One Engine for Live Apps. Data Workers Owns Whether the Data Behind Them Is RightProductYou're on Sisense: Your Analytics Live Inside Your Customers' Product. Data Workers Owns Whether Those Numbers Are RightProductYou're on Slack: Keep Deciding in the Channel, Let Data Workers Do the Data WorkProductYou're on Snowflake Horizon Context: Give Every Cortex Sense Conflict an Owner, and Fix the Data Under ItProductYou're on Snowflake Semantic Views: Keep Every Metric True to the Tables and dbt Models Under ItProductYou're on Soda: It Checks the Data Against the Contract. Data Workers Fixes What Fails ItProductYou're on Amp. Here's how Data Workers builds on itProductYou're on Splunk: It Finds the Log Line. Data Workers Fixes the Data Behind ItProductYou're on SQL Server: Keep Running the Business on It, and Let Data Workers Own What Flows Out of It into AnalyticsProductYou're on SQLMesh: SQLMesh Plans and Applies Your Changes. Data Workers Runs Production Between PlansProductYou're on Starburst: It Queries Data Where It Lives. Data Workers Owns Whether the Data Behind Those Queries Is RightProductYou're on Stardog: Keep the Tables Under Every Virtual Graph True, So Voicebox Answers RightProductYou're on Stitch: The Simple, Low-Cost Way You Replicate SaaS and Database Data. Data Workers Owns Whether It's RightProductYou're on Strategy (MicroStrategy): Mosaic Serves the Governed Metric. Data Workers Owns Whether the Data Under It Is RightProductYou're on StreamNative: It Turns Your Pulsar and Kafka Streams Into Lakehouse Tables. Data Workers Owns Whether Those Tables Are RightProductYou're on Striim: It Streams Every Change in Real Time. Data Workers Owns Whether What Lands Downstream Is RightProductYou're on Superset and Preset: Open-Source Dashboards on the Warehouse. Data Workers Owns Whether the Data Under Them Is RightProductYou're on Tableau: It Is Where the Business Looks at Its Data. Data Workers Owns Whether the Data Behind Every View Is RightProductYou're on Tabnine: private AI coding for data engineering, with Data Workers running every data change inside your environmentProductYou're on Talend: Your Team Builds the Jobs in Qlik Talend Cloud. Data Workers Owns Whether What They Deliver Is RightProductYou're on Telmai: It Trips the Breaker on Bad Lake Data. Data Workers Fixes the Fault and Resets ItProductYou're on Teradata: It Runs Your Enterprise's Most Demanding Analytics. Data Workers Owns Whether What It Serves Is Right, in Place or Through a MoveProductYou're on ThoughtSpot: Anyone Can Ask the Data a Question. Data Workers Owns Whether the Data Behind the Answer Is RightProductYou're on TigerGraph: Keep Your Deep-Link Analytics Right, From the Warehouse Table to the Fraud-Ring QueryProductYou're on Timbr: Keep the Tables Under Every SQL Ontology Mapping True, So Agents Answer RightProductYou're on TopBraid EDG (now TQ Data Foundation): Make Every System Compute What Your Experts ApprovedProductYou're on TrustGraph: Keep Your Context Cores True When the Warehouse Data ChangesProductYou're on Validio: It Finds the Segment That Broke. Data Workers Fixes the CauseProductYou're on Vantage: Vantage Reports and Remediates Cloud Waste. Data Workers Owns Whether the Data That Spend Pays For Is Still RightProductYou're on Varonis: Varonis Watches Who Touches Your Data. Data Workers Makes Sure the Data Is RightProductYou're on Vertica: It Runs High-Speed Analytics for the Teams That Depend on It. Data Workers Owns Whether the Data Behind It Is RightProductYou're on Warp: give its agents governed data context and approved data changesProductYou're on Weaviate: Keep Every Tenant and Collection True, From the Warehouse Feed to the Query Agent AnswerProductYou're on Windsurf (now Devin Desktop). Here's how Data Workers builds on itProductYou're on Writer: Add Data Workers as a Custom Connector So Every Brief, Deck and Dashboard Runs on Governed NumbersProductYou're on Zep: Keep the Facts Your Agents Remember About Data as True as the WarehouseProductYou're on CloudZero: CloudZero Turns Cloud Spend Into Unit Costs the Business Understands. Data Workers Makes Sure the Usage Data Behind Them Is RightProductYou're on Finout: Finout Allocates Every Dollar to the Team That Owns It. Data Workers Owns Whether the Data Behind Those Allocations Is RightProductYou're on Unravel: Unravel Tunes How Your Jobs Run. Data Workers Owns Whether What They Produce Is RightProductYou're on Revefi: Its AI DBA Watches Spend and Quality. Data Workers Fixes What Breaks and Proves ItProductYou're on Espresso AI: It Routes Every Query. Data Workers Keeps the Data and the Cost Trail RightProductYou're on IBM Cloudability: It Gives Finance and Engineering One View of Cloud Spend. Data Workers Owns Whether the Pipelines That Spend Runs Are RightProductYou're on Ternary: Ternary Is the Ledger Finance and Engineering Share. Data Workers Is Accountable for the Data Behind Every LineProductYou're on MLflow: MLflow Keeps the Record of Every Run and Model Version. Data Workers Keeps the Data Under Them RightProductYou're on Amazon SageMaker AI: SageMaker Trains and Serves the Model. Data Workers Fixes the Data Before the Next Training Job Reads ItProductYou're on Weights & Biases: W&B Tracks the Experiments, Artifacts and Evaluations. Data Workers Owns Whether the Data Behind Them Is RightProductYou're on Arize: Arize Watches Your Models and Agents in Production. Data Workers Fixes the Data Behind What It FlagsProductYou're on Tecton: Tecton Computes and Serves the Features. Data Workers Makes Sure the Source Data Behind Them Is RightProductYou're on Feast: Feast Defines and Serves Your Features. Data Workers Makes Sure the Tables Behind Them Are RightProductYou're on DataRobot: DataRobot Builds, Deploys and Governs the Models. Data Workers Owns Whether the Data They Depend On Is RightProductYou're on Domino Data Lab: Domino Runs the Governed Workbench. Data Workers Keeps the Warehouse Data Behind It RightProductYou're on Comet: Opik Scores the Agent and Comet Tracks the Runs. Data Workers Answers for the Data They ReadProductYou're on LangSmith: LangSmith Traces and Evaluates Your Agents. Data Workers Owns Whether the Data They Answer From Is RightComparisonSnowflake CoCo vs the Data-Agents Swarm: an engineer's coding agent vs agents that run the estateComparisonGenie ZeroOps vs the Autonomous Data-Conductor: Fixing Incidents Inside Databricks or Across the EstateComparisonGoogle Data Agent Kit and MCP Toolbox vs Data Workers: Build Your Own Data Agents, or Run a Finished PlatformComparisonFabric Data Agent vs Data Workers: an Agent That Answers, or Agents That Fix What the Answer Depends OnComparisonSnowflake data metric functions vs the Autonomous Data-Conductor: an alert or a resolved incidentTutorialFrom Databricks to an Autonomous Data Platform: A Stage-by-Stage PlaybookTutorialFrom Google Cloud to an Autonomous Data Platform: A Stage-by-Stage PlaybookTutorialFrom Palantir to an Autonomous Data Platform: A Stage-by-Stage PlaybookTutorialFrom Snowflake to an Autonomous Data Platform: A Stage-by-Stage PlaybookComparisonAlready on Databricks? What Data Workers Adds on Top of Genie, Unity Catalog and Agent BricksComparisonOn Google Cloud? What Data Workers Adds on Top of Knowledge Catalog (Formerly Dataplex) and the BigQuery AgentsComparisonAlready on Palantir? What Data Workers Adds Beneath Foundry, AIP and the OntologyComparisonAlready on Snowflake? What Data Workers Adds on Top of Cortex Agents, CoWork, CoCo and HorizonIndustryYou Built on Databricks. Now Make It Agentic & Autonomous with Data WorkersIndustryYou Built on Google Cloud. Now Make Your Whole Estate Agentic & Autonomous with Data WorkersIndustryYour Decisions Run on Palantir. Now Make Your Data Operations Autonomous with Data WorkersIndustryYou Built on Snowflake. Now Make It Agentic & Autonomous with Data WorkersComparisonData observability tools comparison: Bigeye, Anomalo, Sifflet and Soda vs Data WorkersComparisonActioneer vs Data Workers: Agents That Read Your Data, a Platform That Fixes ItComparisonMinusX, PromptQL and TextQL vs Data Workers: AI data analyst tools answer the question, Data Workers makes the answer rightComparisonA Dataplex Alternative for Multi-Platform Teams: Knowledge Catalog vs Spellbook Data CatalogComparisonSnowflake Horizon Context vs Data Workers: One Approved Context for Every Agent, on Every PlatformComparisonUnity Catalog Alternative or Add-On? Unity Catalog vs Spellbook, the Agentic CatalogComparisonAgent Bricks vs the Data-Agents Swarm: Build or Buy Your Data AgentsComparisonAlkera vs Data Workers: An Agent for the Engineer, a Platform for the EstateComparisonGenie Code vs the Data-Agents Swarm: a Copilot in the Notebook, or a Crew That Owns the WorkComparisonBigQuery Data Engineering Agent vs the Data-Agents Swarm: One Agent in Dataform, or Specialists Across the EstateComparisonAltimate AI Alternative: Data Workers Runs the Back Office Around Your dbt WorkComparisonKnowledge Catalog Context for AI Agents vs Data Workers: Gemini Drafts It, a Named Owner Approves ItComparisonData catalog comparison 2026: Collibra, Alation, DataHub and OpenMetadata vs Spellbook Data CatalogComparisonRecce Alternative: Data Workers Reviews the dbt PR, Then Fixes and Verifies What It FindsComparisonDatabricks Unity Gateway and Contextual Service Policies vs Data Workers Autonomy GuardrailsIndustryPricing Report 2026 on the Agentic Data IndustryProductInside the Data Change Review AgentProductInside the Data Security AgentProductInside the Identity AgentProductInside the Cost Savings & Data Cleanup AgentProductInside the Data Migration AgentProductInside the Data Science & Insights AgentProductInside the MLOps & Models AgentProductInside the Observability AgentProductInside the Conductor AgentProductInside the Data Ingestion AgentProductInside the Search & Research AgentProductInside the Usage Intelligence AgentProductInside the Connectors AgentProductInside the Pipeline Building AgentProductInside the Incident Debugging AgentProductInside the Quality Monitoring AgentProductInside the Schema Evolution AgentProductInside the Data Access & Governance AgentProductInside the Real-Time Streaming AgentProductInside the Data Context & Catalog AgentProductMeet the Data Guardrail Agent: Code Review's Missing HalfEngineeringWhat Ralph Kimball's Dimensional Modeling Taught Our Pipelines AgentEngineeringWhat Jay Kreps's Log-Centric Architecture Taught Our Streaming AgentEngineeringWhat W. Edwards Deming's Plan-Do-Study-Act Taught Our Data Quality AgentEngineeringWhat Charity Majors's Wide-Event Method Taught Our Observability AgentEngineeringWhat John Allspaw's Blameless Postmortem Method Taught Our Incident Analysis AgentEngineeringWhat Martin Kleppmann's Evolutionary Compatibility Method Taught Our Schema AgentEngineeringWhat Andrew Ng's Data-Centric AI Method Taught Our Machine Learning AgentEngineeringWhat Martin Fowler's Evolutionary Database Design Taught Our Migration AgentEngineeringWhat Corey Quinn's Architecture-as-Cost Method Taught Our Cost AgentEngineeringWhat DJ Patil's Five-C Ethical Checklist Taught Our Governance AgentEngineeringWhat Bruce Schneier's Adversarial Security Thinking Taught Our Security AgentEngineeringWhat Benn Stancil's Trust-Signal Method Taught Our Context Catalog AgentEngineeringWhat Joe Reis's Data Engineering Lifecycle Taught Our Connectors AgentEngineeringWhat Zhamak Dehghani's Data Mesh Taught Our Catalog AgentEngineeringWhat Gregor Hohpe's Enterprise Integration Patterns Taught Our Connector AgentEngineeringWhat Doug Turnbull's Judgment-First Search Method Taught Our Search AgentEngineeringWhat John Cutler's Data-Informed Product Cycle Taught Our Usage Intelligence AgentEngineeringWhat Simon Willison's Friction-Free Learning Method Taught Our Open-Source AgentEngineeringWhat Glenn McDonald's Data Alchemy Taught Our Analytics AgentEngineeringWhat Maxime Beauchemin's Functional Data Engineering Taught Our Orchestration AgentComparisonAtlan Alternatives: 6 Open-Source Data Catalogs Compared (2026)TutorialMCP Servers for BI Tools: Looker, Tableau, Power BI, Mode (2026)TutorialHow to Give Claude Access to Snowflake Without Exposing PIIProductWhy AI Agents Hallucinate on Your Data (And How to Fix It)EngineeringDear Open Claw: Your Data Stack Is Now an MCP Call AwayEngineeringWhy We Open-Sourced 14 Autonomous Data Engineering AgentsIndustryWhy Every MCP Server for MLOps Is Read-Only (And Why That Is About to Change)IndustryThe Context and Semantic Layer Market: Why Nobody Has Solved This YetIndustryWhy Your Data Stack Needs an ML Agent (Not Just a Notebook)IndustryWhat We Learned Studying the Data Engineering Market Before BuildingEngineeringWhy We Bet on MCP (And What We're Still Figuring Out)IndustryWhy Your Data Stack Still Needs Humans at 2 AMEngineeringWhy Your 200 DAGs Need a Brain (Not Another Dashboard)ProductCopilots, Agents, and Swarms: A Decision Framework for Data TeamsEngineeringYour Data Governance Is a PDF Nobody ReadsEngineeringBuilding an Incident Debugging Agent: What We've Learned So FarProductOur Agent Roadmap: What We've Built, What We're Building, and Why