Fivetran

Overview
HQ Location
United States
|
Year Founded
2012
|
Company Type
Private
|
Revenue
< $10m
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Employees
51 - 200
|
Website
|
Twitter Handle
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Company Description
FiveTran offers integrations built and online data analysis services Integrations for data analysts. Their technology is shaped by the real-world needs of data analysts and supports agile analytics, enabling data-backed decisions across organizations. Fivetran began with a realization: For modern companies using cloud-based software and storage, traditional ETL tools badly underperformed, and the complicated configurations they required often led to project failures.
Fivetran fully automated connectors sync data from cloud applications, databases, event logs and more into users' data warehouse. Its integrations are built for analysts who need data centralized but don’t want to spend time maintaining their own pipelines or ETL systems. The company delivers its services via spreadsheet function.
Fivetran fully automated connectors sync data from cloud applications, databases, event logs and more into users' data warehouse. Its integrations are built for analysts who need data centralized but don’t want to spend time maintaining their own pipelines or ETL systems. The company delivers its services via spreadsheet function.
IoT Solutions
Fivetran helps analysts replicate data into a cloud warehouse.
We make replication effortless
Fivetran handles 100% of your pipeline maintenance and setup.
- Built for analysts, approved by engineers.
- Replicate everything, with zero configuration and schemas designed for analytics. Eliminate engineering busywork while empowering your analysts to prove value.
- Five-minute setup. 10 clicks and you’re syncing data into your warehouse.
- Ready-to-query data. We prep your data so you can run analytics instantly:
- Support for modern cloud warehouses
- Built to scale
- Next-level enterprise security
We make replication effortless
Fivetran handles 100% of your pipeline maintenance and setup.
- Built for analysts, approved by engineers.
- Replicate everything, with zero configuration and schemas designed for analytics. Eliminate engineering busywork while empowering your analysts to prove value.
- Five-minute setup. 10 clicks and you’re syncing data into your warehouse.
- Ready-to-query data. We prep your data so you can run analytics instantly:
- Support for modern cloud warehouses
- Built to scale
- Next-level enterprise security
Key Customers
Talkdesk, Shopkeep, DonorsChoose, Sharethrough, Managed by Q, Fast Spring, , etc.
IoT Snapshot
Fivetran is a provider of Industrial IoT platform as a service (paas), application infrastructure and middleware, and analytics and modeling technologies, and also active in the buildings, and transportation industries.
Technologies
Use Cases
Industries
Services
Technology Stack
Fivetran’s Technology Stack maps Fivetran’s participation in the platform as a service (paas), application infrastructure and middleware, and analytics and modeling IoT Technology stack.
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Devices Layer
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Edge Layer
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Cloud Layer
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Application Layer
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Supporting Technologies
Technological Capability:
None
Minor
Moderate
Strong
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Case Studies.

Case Study
A Construction Marketplace, Uses Fivetran as its Digital Building Block
Enabling data-driven decision makingLaunched in 2018 with a clear mission, Schüttflix wanted to bring digital processes to ‘a pen and paper industry’ and transform highly localized supply chains. The founders knew that data would be important, providing internal and external stakeholders with the best data to make informed decisions. Tasked with building a modern data stack, Alexander Rupp, Head of Data and Business Intelligence, started by evaluating the connectors that could tap into key data sources. Fivetran emerged as the best fit for the business because it was fast and reliable. Rupp was setting up connectors in an hour, something that would have taken weeks otherwise.

Case Study
Lendi Makes Data-driven Decisions with Fivetran
Building an accurate profile of each customer requires tapping into behavioral data on third-party engagement platforms such as Facebook, Google and Bing. This data is readily available to Lendi, but the insights from each platform are siloed and don’t integrate very easily. Even when the data can be brought into the same repository, the data structure is often inconsistent, creating the need to clean the data before it can be put to use. Making sure stakeholders from across the company — marketers, accountants, brokers and customer service reps, for example — are able to analyze and create actionable insights from third-party data is the responsibility of Daniel Deng, Lendi’s Data Architect.
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