Fivetran
https://fivetran.com/
Oakland, CA, USA
2012
fivetran
Beyond centralization: Why APAC retail and CPG teams need dbt
  |  By Shounak Vijay
Learn how dbt helps APAC retail and CPG teams test, govern, and trace their data before it drives critical inventory, promotion, and reordering decisions.
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How to solve ecommerce analytics without manual reporting
  |  By Annie Sullivan
Automate the way you use data to understand customers, predict demand, and optimize supply chains.
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6 ways Open Data Infrastructure accelerates your workflows
  |  By Ciara Rafferty
Six ways Open Data Infrastructure removes friction from your workflows.
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How AI changed performance engineering (2 years later)
  |  By Mike Gordon
We thought the lemon had no more juice. AI proved us wrong.
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The evolving role of the CDO in the AI era
  |  By Charles Wang
The CDO’s job can be boiled down to ensuring data access, building innovative data products, and managing data responsibly.
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How we do performance engineering at Fivetran
  |  By Mike Gordon
We were asked to make Fivetran faster than we thought possible.
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Build vs. buy data pipelines: Costs to consider
  |  By Charles Wang
A few simple calculations illustrate why it's ill-advised to build your own data pipeline.
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5 things to know about where Fivetran sends your data
  |  By David Millman
The destination determines how easily data can be governed, queried, activated, and reused across analytics, AI, and business operations — making it one of the most important decisions in your data architecture.
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dbt Wizard: an AI agent that actually understands your dbt project
  |  By Garegin Ordyan
Data modeling is easier with coding assistants that actually understand the projects they’re working on.
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5 Reasons dbt Wizard transforms your partner practice
  |  By David Millman
dbt Wizard brings conversational AI to analytics and context engineering, grounded in your dbt project’s lineage, compiled state, tests, and semantics.
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Stop your AI agent's $100,000 reordering mistake
  |  By Fivetran
See how Fivetran and dbt help an AI reordering agent make more reliable retail decisions. This end-to-end demo shows how trusted data supports smarter inventory decisions across the enterprise.
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Building an AI-ready data foundation at Superhuman with Databricks and Fivetran
  |  By Fivetran
As Superhuman expanded its AI platform across Grammarly, Coda, Superhuman Mail, and Superhuman Go, more of the business began to rely on timely data from Salesforce, Outreach, Pardot, Stripe, Zendesk, Qualtrics, and other third-party systems. The challenge went far beyond moving data into Databricks. Go-to-market, finance, and customer teams needed faster, reliable access to trusted data without turning every new data request into weeks of custom engineering.
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Open Data Infrastructure: Built for agentic AI
  |  By Fivetran
As AI accelerates the pace of change, demanding fresher data, diverse formats, and support across multiple engines, many teams discover their infrastructure was built for reporting, not real-time AI at scale. Open Data Infrastructure is redefining how organizations design for analytics, operations, and AI. By leveraging Fivetran as an interoperable data foundation, organizations can embrace open standards, separate storage from compute, and keep data portable across clouds and engines, preserving adaptability while scaling AI and operational workloads with Databricks.
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From Backlog to Breakthrough: Inova Scales Data & AI with Fivetran and Databricks
  |  By Fivetran
Healthcare organizations operate some of the most complex data environments, spanning thousands of systems across clinical, financial, and operational domains. At Inova Health, this complexity created an opportunity to rethink how data could better support analytics and AI at scale.
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Build a multi tool agent
  |  By Fivetran
And get Fivetran’s latest news at.
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Standardize data with consistent models
  |  By Fivetran
And get Fivetran’s latest news at.
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Store data in an open, AI ready foundation
  |  By Fivetran
And get Fivetran’s latest news at.
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Fivetran Activations Demo
  |  By Fivetran
Learn how Fivetran activates data and delivers it into business applications for analytics, insights, and customer segmentation.
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How to dynamically map source files to tables using Fivetran File connectors
  |  By Fivetran
And get Fivetran’s latest news at.
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How to use the Fivetran Managed Data Lake Service to set up ADLS
  |  By Fivetran
How to use the Fivetran Managed Data Lake Service to set up ADLS.
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Fivetran fully automated connectors sync data from cloud applications, databases, event logs and more into your data warehouse. Our integrations are built for analysts who need data centralized but don’t want to spend time maintaining their own pipelines or ETL systems.

Focus on analytics, not engineering. Our prebuilt connectors deliver analysis-ready schemas and adapt to source changes automatically.

Keep your team focused on analysis:

  • Prebuilt connectors: Centralize your operational data in minutes with 150+ zero-configuration connectors.
  • Ready-to-query schemas: Use thoughtful, research-driven schemas and ERDs for all your sources.
  • Automated schema migrations: Save resources with connectors that automatically adapt to schema and API changes.
  • Fully managed data integration: Reduce technical debt with scalable connectors managed from source to destination.
  • SQL-based transformations: Model your business logic in any destination using SQL, the industry standard.
  • Incremental batch updates: Change data capture delivers incremental updates for all your sources.

Simple, reliable data integration for analytics teams.

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